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Entry Level | On-Site | Pune
Internship Opportunity: Data + AI Intern
Location: Pune, India (In-office)
Duration: 2 Months
Start Date: Between 11th July 2025 and 15th August 2025
Work Days: Monday to Friday
Stipend: As per company policy
About ImmersiveData.AI
Smarter Data. Smarter Decisions. Smarter Enterprises.™
At ImmersiveData.AI, we don’t just transform data—we challenge and redefine business models. By leveraging cutting-edge AI, intelligent automation, and modern data platforms, we empower enterprises to unlock new value and drive strategic transformation.
About the Internship
As a Data + AI Intern, you will gain hands-on experience at the intersection of data engineering and AI. You’ll be part of a collaborative team working on real-world data challenges using modern tools like Snowflake, DBT, Airflow, and LLM frameworks. This internship is a launchpad for students looking to enter the rapidly evolving field of Data & AI.
Key Responsibilities
- Assist in designing, building, and optimizing data pipelines and ETL workflows
- Work with structured and unstructured datasets across various sources
- Contribute to AI-driven automation and analytics use cases
- Support backend integration of large language models (LLMs)
- Collaborate in building data platforms using tools like Snowflake, DBT, and Airflow
Required Skills
- Proficiency in Python
- Strong understanding of SQL and relational databases
- Basic knowledge of Data Engineering and Data Analysis concepts
- Familiarity with cloud data platforms or willingness to learn (e.g., Snowflake)
Preferred Learning Certifications (Optional but Recommended)
- Python Programming
- SQL & MySQL/PostgreSQL
- Statistical Modeling
- Tableau / Power BI
- Voice App Development (Bonus)
Who Can Apply
Only candidates who:
- Are available full-time (in-office, Pune)
- Can start between 11th July and 15th August 2025
- Are available for a minimum of 2 months
- Have relevant skills and interest in data and AI
Perks
- Internship Certificate
- Letter of Recommendation
- Work with cutting-edge tools and technologies
- Informal dress code
- Exposure to real industry use cases and mentorship
EMPLOYMENT TYPE: Full-Time, Permanent
LOCATION: Remote
SHIFT TIMINGS: 11.00 AM - 8:00 PM IST
Role : Lead Data Analyst
Qualifications:
● Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Systems, or a related field.
● 7–10 years of experience in data operations, data management, or analytics.
● Strong understanding of data governance, ETL processes, and quality control methodologies.
● Hands-on experience with SQL, Excel/Google Sheets, and data visualization tools
● Experience with automation tools like Python script is a plus.
● Must be capable of working independently and delivering stable, efficient and reliable software.
● Excellent written and verbal communication skills in English.
● Experience supporting and working with cross-functional teams in a dynamic environment
Preferred Skills:
● Experience in SaaS, B2B data, or lead intelligence industry.
● Exposure to data privacy regulations (GDPR, CCPA) and compliance practices.
● Ability to work effectively in cross-functional, global, and remote environments.
We are seeking a Technical Lead with strong expertise in backend engineering, real-time data streaming, and platform/infrastructure development to lead the architecture and delivery of our on-premise systems.
You will design and build high-throughput streaming pipelines (Apache Pulsar, Apache Flink), backend services (FastAPI), data storage models (MongoDB, ClickHouse), and internal dashboards/tools (Angular).
In this role, you will guide engineers, drive architectural decisions, and ensure reliable systems deployed on Docker + Kubernetes clusters.
Key Responsibilities
1. Technical Leadership & Architecture
- Own the end-to-end architecture for backend, streaming, and data systems.
- Drive system design decisions for ingestion, processing, storage, and DevOps.
- Review code, enforce engineering best practices, and ensure production readiness.
- Collaborate closely with founders and domain experts to translate requirements into technical deliverables.
2. Data Pipeline & Streaming Systems
- Architect and implement real-time, high-throughput data pipelines using Apache Pulsar and Apache Flink.
- Build scalable ingestion, enrichment, and stateful processing workflows.
- Integrate multi-sensor maritime data into reliable, unified streaming systems.
3. Backend Services & Platform Engineering
- Lead development of microservices and internal APIs using FastAPI (or equivalent backend frameworks).
- Build orchestration, ETL, and system-control services.
- Optimize backend systems for latency, throughput, resilience, and long-term maintainability.
4. Data Storage & Modeling
- Design scalable, efficient data models using MongoDB, ClickHouse, and other on-prem databases.
- Implement indexing, partitioning, retention, and lifecycle strategies for large datasets.
- Ensure high-performance APIs and analytics workflows.
5. Infrastructure, DevOps & Containerization
- Deploy and manage distributed systems using Docker and Kubernetes.
- Own observability, monitoring, logging, and alerting for all critical services.
- Implement CI/CD pipelines tailored for on-prem and hybrid cloud environments.
6. Team Management & Mentorship
- Provide technical guidance to engineers across backend, data, and DevOps teams.
- Break down complex tasks, review designs, and ensure high-quality execution.
- Foster a culture of clarity, ownership, collaboration, and engineering excellence.
Required Skills & Experience
- 5–10+ years of strong software engineering experience.
- Expertise with streaming platforms like Apache Pulsar, Apache Flink, or similar technologies.
- Strong backend engineering proficiency — preferably FastAPI, Python, Java, or Scala.
- Hands-on experience with MongoDB and ClickHouse.
- Solid experience deploying, scaling, and managing services on Docker + Kubernetes.
- Strong understanding of distributed systems, high-performance data flows, and system tuning.
- Experience working with Angular for internal dashboards is a plus.
- Excellent system-design, debugging, and performance-optimization skills.
- Prior experience owning critical technical components or leading engineering teams.
Nice to Have
- Experience with sensor data (AIS, Radar, SAR, EO/IR).
- Exposure to maritime, defence, or geospatial technology.
- Experience with bare-metal / on-premise deployments.
Core Responsibilities:
- The MLE will design, build, test, and deploy scalable machine learning systems, optimizing model accuracy and efficiency
- Model Development: Algorithms and architectures span traditional statistical methods to deep learning along with employing LLMs in modern frameworks.
- Data Preparation: Prepare, cleanse, and transform data for model training and evaluation.
- Algorithm Implementation: Implement and optimize machine learning algorithms and statistical models.
- System Integration: Integrate models into existing systems and workflows.
- Model Deployment: Deploy models to production environments and monitor performance.
- Collaboration: Work closely with data scientists, software engineers, and other stakeholders.
- Continuous Improvement: Identify areas for improvement in model performance and systems.
Skills:
- Programming and Software Engineering: Knowledge of software engineering best practices (version control, testing, CI/CD).
- Data Engineering: Ability to handle data pipelines, data cleaning, and feature engineering. Proficiency in SQL for data manipulation + Kafka, Chaossearch logs, etc for troubleshooting; Other tech touch points are ScyllaDB (like BigTable), OpenSearch, Neo4J graph
- Model Deployment and Monitoring: MLOps Experience in deploying ML models to production environments.
- Knowledge of model monitoring and performance evaluation.
Required experience:
- Amazon SageMaker: Deep understanding of SageMaker's capabilities for building, training, and deploying ML models; understanding of the Sagemaker pipeline with ability to analyze gaps and recommend/implement improvements
- AWS Cloud Infrastructure: Familiarity with S3, EC2, Lambda and using these services in ML workflows
- AWS data: Redshift, Glue
- Containerization and Orchestration: Understanding of Docker and Kubernetes, and their implementation within AWS (EKS, ECS)
Skills: Aws, Aws Cloud, Amazon Redshift, Eks
Must-Haves
Machine Learning +Aws+ (EKS OR ECS OR Kubernetes) + (Redshift AND Glue) + Sagemaker
Notice period - 0 to 15days only
Hybrid work mode- 3 days office, 2 days at home
Review Criteria
- Strong Dremio / Lakehouse Data Architect profile
- 5+ years of experience in Data Architecture / Data Engineering, with minimum 3+ years hands-on in Dremio
- Strong expertise in SQL optimization, data modeling, query performance tuning, and designing analytical schemas for large-scale systems
- Deep experience with cloud object storage (S3 / ADLS / GCS) and file formats such as Parquet, Delta, Iceberg along with distributed query planning concepts
- Hands-on experience integrating data via APIs, JDBC, Delta/Parquet, object storage, and coordinating with data engineering pipelines (Airflow, DBT, Kafka, Spark, etc.)
- Proven experience designing and implementing lakehouse architecture including ingestion, curation, semantic modeling, reflections/caching optimization, and enabling governed analytics
- Strong understanding of data governance, lineage, RBAC-based access control, and enterprise security best practices
- Excellent communication skills with ability to work closely with BI, data science, and engineering teams; strong documentation discipline
- Candidates must come from enterprise data modernization, cloud-native, or analytics-driven companies
Preferred
- Preferred (Nice-to-have) – Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) or data catalogs (Collibra, Alation, Purview); familiarity with Snowflake, Databricks, or BigQuery environments
Job Specific Criteria
- CV Attachment is mandatory
- How many years of experience you have with Dremio?
- Which is your preferred job location (Mumbai / Bengaluru / Hyderabad / Gurgaon)?
- Are you okay with 3 Days WFO?
- Virtual Interview requires video to be on, are you okay with it?
Role & Responsibilities
You will be responsible for architecting, implementing, and optimizing Dremio-based data lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.
- Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
- Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
- Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
- Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
- Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
- Support self-service analytics by enabling governed data products and semantic layers.
- Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
- Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.
Ideal Candidate
- Bachelor’s or master’s in computer science, Information Systems, or related field.
- 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
- Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
- Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
- Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
- Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
- Excellent problem-solving, documentation, and stakeholder communication skills.
Role: Senior Data Engineer (Azure)
Experience: 5+ Years
Location: Anywhere in india
Work Mode: Remote
Notice Period - Immediate joiners or Serving notice period
𝐊𝐞𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬:
- Data processing on Azure using ADF, Streaming Analytics, Event Hubs, Azure Databricks, Data Migration Services, and Data Pipelines
- Provisioning, configuring, and developing Azure solutions (ADB, ADF, ADW, etc.)
- Designing and implementing scalable data models and migration strategies
- Working on distributed big data batch or streaming pipelines (Kafka or similar)
- Developing data integration & transformation solutions for structured and unstructured data
- Collaborating with cross-functional teams for performance tuning and optimization
- Monitoring data workflows and ensuring compliance with governance and quality standards
- Driving continuous improvement through automation and DevOps practices
𝐌𝐚𝐧𝐝𝐚𝐭𝐨𝐫𝐲 𝐒𝐤𝐢𝐥𝐥𝐬 & 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞:
- 5–10 years of experience as a Data Engineer
- Strong proficiency in Azure Databricks, PySpark, Python, SQL, and Azure Data Factory
- Experience in Data Modelling, Data Migration, and Data Warehousing
- Good understanding of database structure principles and schema design
- Hands-on experience with MS SQL Server, Oracle, or similar RDBMS platforms
- Experience with DevOps tools (Azure DevOps, Jenkins, Airflow, Azure Monitor) — good to have
- Knowledge of distributed data processing and real-time streaming (Kafka/Event Hub)
- Familiarity with visualization tools like Power BI or Tableau
- Strong analytical, problem-solving, and debugging skills
- Self-motivated, detail-oriented, and capable of managing priorities effectively
Technical Project Manager
As a Technical Project Manager, you will be leading a team to build a highly scalable and extensible big data platform that provides the foundation for collecting, storing, modelling, and analysing massive data sets from multiple channels.
Responsibilities
1. Align Sigmoid with key Client initiatives
- Interface daily with customers across leading Fortune 500 companies to understand strategic requirements.
- Connect with CIO, VP, and Director level clients on a regular basis.
- Travel to client locations.
- Ability to understand business requirements and tie them to technology solutions.
2. Build a delivery plan with domain experts and stay on track
- Design, develop and evolve highly scalable and fault-tolerant distributed components using Big Data technologies.
- Excellent experience in application development and support, integration development, and data management.
3. Build team and manage it on a day-to-day basis
- Play the key role of hiring manager to build the future of Sigmoid.
- Guide developers in day-to-day design and coding tasks, stepping into code if needed.
- Define your team structure, hire, and train your team as needed.
4. Stay up to date on the latest technology to ensure the greatest ROI for customer & Sigmoid
- Hands-on coder with good understanding of enterprise-level code.
- Design and implement APIs, abstractions, and integration patterns to solve challenging distributed computing problems.
- Experience in defining technical requirements, data extraction, data transformation, automating jobs, productionizing jobs, and exploring new big data technologies within a Parallel Processing environment.
5. Culture
- Must be a strategic thinker with the ability to think unconventional / out-of-box.
- Analytical and data-driven orientation.
- Raw intellect, talent, and energy are critical.
- Entrepreneurial and Agile: understands the demands of a private, high-growth company.
- Ability to be both a leader and hands-on "doer".
Qualifications
- 7+ years track record of relevant work experience and a Computer Science or related technical discipline is required.
- Dynamic leader who has directly managed a team of highly competent developers in a fast-paced work environment.
- Experience in architecture and delivery of enterprise-scale applications.
Preferred Qualifications
- Experience in Agile methodology.
- Development and support experience in Big Data domain.
- Architecting, developing, implementing, and maintaining Big Data solutions.
- Experience with database modelling and development, data mining, and warehousing.
- Experience with Hadoop ecosystem (HDFS, MapReduce, Oozie, Hive, Impala, Spark, Kerberos, Kafka, etc).
Strong Data engineer profile
Mandatory (Experience 1): Must have 6 months+ of hands-on Data Engineering experience.
Mandatory (Experience 2): Must have end-to-end experience in building & maintaining ETL/ELT pipelines (not just BI/reporting).
Mandatory (Technical): Must have strong SQL capability
Preferred
Preferred (Experience): Worked on Call center data
Job Specific Criteria
CV Attachment is mandatory
Have you used Databricks or any notebook environment?
Have you worked on ETL/ELT workflow?
We have an alternate Saturdays working. Are you comfortable to WFH on 1st and 4th Saturday?
Role: Azure Fabric Data Engineer
Experience: 5–10 Years
Location: Pune/Bangalore
Employment Type: Full-Time
About the Role
We are looking for an experienced Azure Data Engineer with strong expertise in Microsoft Fabric and Power BI to build scalable data pipelines, Lakehouse architectures, and enterprise analytics solutions on the Azure cloud.
Key Responsibilities
- Design & build data pipelines using Microsoft Fabric (Pipelines, Dataflows Gen2, Notebooks).
- Develop and optimize Lakehouse / Data Lake / Delta Lake architectures.
- Build ETL/ELT workflows using Fabric, Azure Data Factory, or Synapse.
- Create and optimize Power BI datasets, data models, and DAX calculations.
- Implement semantic models, incremental refresh, and Direct Lake/DirectQuery.
- Work with Azure services: ADLS Gen2, Azure SQL, Synapse, Event Hub, Functions, Databricks.
- Build dimensional models (Star/Snowflake) and support BI teams.
- Ensure data governance & security using Purview, RBAC, and AAD.
Required Skills
- Strong hands-on experience with Microsoft Fabric (Lakehouse, Pipelines, Dataflows, Notebooks).
- Expertise in Power BI (DAX, modeling, Dataflows, optimized datasets).
- Deep knowledge of Azure Data Engineering stack (ADF, ADLS, Synapse, SQL).
- Strong SQL, Python/PySpark skills.
- Experience in Delta Lake, Medallion architecture, and data quality frameworks.
Nice to Have
- Azure Certifications (DP-203, PL-300, Fabric Analytics Engineer).
- Experience with CI/CD (Azure DevOps/GitHub).
- Databricks experience (preferred).
Note: One Technical round is mandatory to be taken F2F from either Pune or Bangalore office
Review Criteria
- Strong Senior Data Engineer profile
- 4+ years of hands-on Data Engineering experience
- Must have experience owning end-to-end data architecture and complex pipelines
- Must have advanced SQL capability (complex queries, large datasets, optimization)
- Must have strong Databricks hands-on experience
- Must be able to architect solutions, troubleshoot complex data issues, and work independently
- Must have Power BI integration experience
- CTC has 80% fixed and 20% variable in their ctc structure
Preferred
- Worked on Call center data, understand nuances of data generated in call centers
- Experience implementing data governance, quality checks, or lineage frameworks
- Experience with orchestration tools (Airflow, ADF, Glue Workflows), Python, Delta Lake, Lakehouse architecture
Job Specific Criteria
- CV Attachment is mandatory
- Are you Comfortable integrating with Power BI datasets?
- We have an alternate Saturdays working. Are you comfortable to WFH on 1st and 4th Saturday?
Role & Responsibilities
We are seeking a highly experienced Senior Data Engineer with strong architectural capability, excellent optimisation skills, and deep hands-on experience in modern data platforms. The ideal candidate will have advanced SQL skills, strong expertise in Databricks, and practical experience working across cloud environments such as AWS and Azure. This role requires end-to-end ownership of complex data engineering initiatives, including architecture design, data governance implementation, and performance optimisation. You will collaborate with cross-functional teams to build scalable, secure, and high-quality data solutions.
Key Responsibilities-
- Lead the design and implementation of scalable data architectures, pipelines, and integration frameworks.
- Develop, optimise, and maintain complex SQL queries, transformations, and Databricks-based data workflows.
- Architect and deliver high-performance ETL/ELT processes across cloud platforms.
- Implement and enforce data governance standards, including data quality, lineage, and access control.
- Partner with analytics, BI (Power BI), and business teams to enable reliable, governed, and high-value data delivery.
- Optimise large-scale data processing, ensuring efficiency, reliability, and cost-effectiveness.
- Monitor, troubleshoot, and continuously improve data pipelines and platform performance.
- Mentor junior engineers and contribute to engineering best practices, standards, and documentation.
Ideal Candidate
- Proven industry experience as a Senior Data Engineer, with ownership of high-complexity projects.
- Advanced SQL skills with experience handling large, complex datasets.
- Strong expertise with Databricks for data engineering workloads.
- Hands-on experience with major cloud platforms — AWS and Azure.
- Deep understanding of data architecture, data modelling, and optimisation techniques.
- Familiarity with BI and reporting environments such as Power BI.
- Strong analytical and problem-solving abilities with a focus on data quality and governance
- Proficiency in python or another programming language in a plus.
ROLES AND RESPONSIBILITIES:
We are seeking a highly experienced Senior Data Engineer with strong architectural capability, excellent optimisation skills, and deep hands-on experience in modern data platforms. The ideal candidate will have advanced SQL skills, strong expertise in Databricks, and practical experience working across cloud environments such as AWS and Azure. This role requires end-to-end ownership of complex data engineering initiatives, including architecture design, data governance implementation, and performance optimisation. You will collaborate with cross-functional teams to build scalable, secure, and high-quality data solutions.
Key Responsibilities-
- Lead the design and implementation of scalable data architectures, pipelines, and integration frameworks.
- Develop, optimise, and maintain complex SQL queries, transformations, and Databricks-based data workflows.
- Architect and deliver high-performance ETL/ELT processes across cloud platforms.
- Implement and enforce data governance standards, including data quality, lineage, and access control.
- Partner with analytics, BI (Power BI), and business teams to enable reliable, governed, and high-value data delivery.
- Optimise large-scale data processing, ensuring efficiency, reliability, and cost-effectiveness.
- Monitor, troubleshoot, and continuously improve data pipelines and platform performance.
- Mentor junior engineers and contribute to engineering best practices, standards, and documentation.
IDEAL CANDIDATE:
- Proven industry experience as a Senior Data Engineer, with ownership of high-complexity projects.
- Advanced SQL skills with experience handling large, complex datasets.
- Strong expertise with Databricks for data engineering workloads.
- Hands-on experience with major cloud platforms — AWS and Azure.
- Deep understanding of data architecture, data modelling, and optimisation techniques.
- Familiarity with BI and reporting environments such as Power BI.
- Strong analytical and problem-solving abilities with a focus on data quality and governance
- Proficiency in python or another programming language in a plus.
PERKS, BENEFITS AND WORK CULTURE:
Our people define our passion and our audacious, incredibly rewarding achievements. The company is one of India’s most diversified Non-banking financial companies, and among Asia’s top 10 Large workplaces. If you have the drive to get ahead, we can help find you an opportunity at any of the 500+ locations we’re present in India.
ROLES AND RESPONSIBILITIES:
We are looking for a Junior Data Engineer who will work under guidance to support data engineering tasks, perform basic coding, and actively learn modern data platforms and tools. The ideal candidate should have foundational SQL knowledge, basic exposure to Databricks. This role is designed for early-career professionals who are eager to grow into full data engineering responsibilities while contributing to data pipeline operations and analytical support.
Key Responsibilities-
- Support the development and maintenance of data pipelines and ETL/ELT workflows under mentorship.
- Write basic SQL queries, transformations, and assist with Databricks notebook tasks.
- Help troubleshoot data issues and contribute to ensuring pipeline reliability.
- Work with senior engineers and analysts to understand data requirements and deliver small tasks.
- Assist in maintaining documentation, data dictionaries, and process notes.
- Learn and apply data engineering best practices, coding standards, and cloud fundamentals.
- Support basic tasks related to Power BI data preparation or integrations as needed.
IDEAL CANDIDATE:
- Foundational SQL skills with the ability to write and understand basic queries.
- Basic exposure to Databricks, data transformation concepts, or similar data tools.
- Understanding of ETL/ELT concepts, data structures, and analytical workflows.
- Eagerness to learn modern data engineering tools, technologies, and best practices.
- Strong problem-solving attitude and willingness to work under guidance.
- Good communication and collaboration skills to work with senior engineers and analysts.
PERKS, BENEFITS AND WORK CULTURE:
Our people define our passion and our audacious, incredibly rewarding achievements. Bajaj Finance Limited is one of India’s most diversified Non-banking financial companies, and among Asia’s top 10 Large workplaces. If you have the drive to get ahead, we can help find you an opportunity at any of the 500+ locations we’re present in India.
- Strong Senior Data Engineer profile
- Mandatory (Experience 1): Must have 4+ years of hands-on Data Engineering experience
- Mandatory (Experience 2): Must have experience owning end-to-end data architecture and complex pipelines
- Mandatory (Technical 1): Must have advanced SQL capability (complex queries, large datasets, optimization)
- Mandatory (Technical 2): Must have strong Databricks hands-on experience
- Mandatory (Role Requirement): Must be able to architect solutions, troubleshoot complex data issues, and work independently
- Mandatory (BI Requirement): Must have Power BI integration experience
- Mandatory (Note): Bajaj CTC has 80% fixed and 20% variable
Strong Data engineer profile
Mandatory (Experience 1): Must have 6 months+ of hands-on Data Engineering experience.
Mandatory (Experience 2): Must have end-to-end experience in building & maintaining ETL/ELT pipelines (not just BI/reporting).
Mandatory (Technical): Must have strong SQL capability
About the Company
Hypersonix.ai is disrupting the e-commerce space with AI, ML and advanced decision capabilities to drive real-time business insights. Hypersonix.ai has been built ground up with new age technology to simplify the consumption of data for our customers in various industry verticals. Hypersonix.ai is seeking a well-rounded, hands-on product leader to help lead product management of key capabilities and features.
About the Role
We are looking for talented and driven Data Engineers at various levels to work with customers to build the data warehouse, analytical dashboards and ML capabilities as per customer needs.
Roles and Responsibilities
- Create and maintain optimal data pipeline architecture
- Assemble large, complex data sets that meet functional / non-functional business requirements; should write complex queries in an optimized way
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies
- Run ad-hoc analysis utilizing the data pipeline to provide actionable insights
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs
- Keep our data separated and secure across national boundaries through multiple data centers and AWS regions
- Work with analytics and data scientist team members and assist them in building and optimizing our product into an innovative industry leader
Requirements
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
- Strong analytic skills related to working with unstructured datasets
- Build processes supporting data transformation, data structures, metadata, dependency and workload management
- A successful history of manipulating, processing and extracting value from large disconnected datasets
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
- Experience supporting and working with cross-functional teams in a dynamic environment
- We are looking for a candidate with 4+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Information Technology or completed MCA.
We are seeking a highly skilled Senior Data Engineer with expertise in Databricks, Python, Scala, Azure Synapse, and Azure Data Factory to join our data engineering team. The team is responsible for ingesting data from multiple sources, making it accessible to internal stakeholders, and enabling seamless data exchange across internal and external systems.
You will play a key role in enhancing and scaling our Enterprise Data Platform (EDP) hosted on Azure and built using modern technologies such as Databricks, Synapse, Azure Data Factory (ADF), ADLS Gen2, Azure DevOps, and CI/CD pipelines.
Responsibilities
- Design, develop, optimize, and maintain scalable data architectures and pipelines aligned with ETL principles and business goals.
- Collaborate across teams to build simple, functional, and scalable data solutions.
- Troubleshoot and resolve complex data issues to support business insights and organizational objectives.
- Build and maintain data products to support company-wide usage.
- Advise, mentor, and coach data and analytics professionals on standards and best practices.
- Promote reusability, scalability, operational efficiency, and knowledge-sharing within the team.
- Develop comprehensive documentation for data engineering standards, processes, and capabilities.
- Participate in design and code reviews.
- Partner with business analysts and solution architects on enterprise-level technical architectures.
- Write high-quality, efficient, and maintainable code.
Technical Qualifications
- 5–8 years of progressive data engineering experience.
- Strong expertise in Databricks, Python, Scala, and Microsoft Azure services including Synapse & Azure Data Factory (ADF).
- Hands-on experience with data pipelines across multiple source & target systems (Databricks, Synapse, SQL Server, Data Lake, SQL/NoSQL sources, and file-based systems).
- Experience with design patterns, code refactoring, CI/CD, and building scalable data applications.
- Experience developing batch ETL pipelines; real-time streaming experience is a plus.
- Solid understanding of data warehousing, ETL, dimensional modeling, data governance, and handling both structured and unstructured data.
- Deep understanding of Synapse and SQL Server, including T-SQL and stored procedures.
- Proven experience working effectively with cross-functional teams in dynamic environments.
- Experience extracting, processing, and analyzing large / complex datasets.
- Strong background in root cause analysis for data and process issues.
- Advanced SQL proficiency and working knowledge of a variety of database technologies.
- Knowledge of Boomi is an added advantage.
Core Skills & Competencies
- Excellent analytical and problem-solving abilities.
- Strong communication and cross-team collaboration skills.
- Self-driven with the ability to make decisions independently.
- Innovative mindset and passion for building quality data solutions.
- Ability to understand operational systems, identify gaps, and propose improvements.
- Experience with large-scale data ingestion and engineering.
- Knowledge of CI/CD pipelines (preferred).
- Understanding of Python and parallel processing frameworks (MapReduce, Spark, Scala).
- Familiarity with Agile development methodologies.
Education
- Bachelor’s degree in Computer Science, Information Technology, MIS, or an equivalent field.
Google Data Engineer - SSE
Position Description
Google Cloud Data Engineer
Notice Period: Immediate to 30 days serving
Job Description:
We are seeking a highly skilled Data Engineer with extensive experience in Google Cloud Platform (GCP) data services and big data technologies. The ideal candidate will be responsible for designing, implementing, and optimizing scalable data solutions while ensuring high performance, reliability, and security.
Key Responsibilities:
• Design, develop, and maintain scalable data pipelines and architectures using GCP data services.
• Implement and optimize solutions using BigQuery, Dataproc, Composer, Pub/Sub, Dataflow, GCS, and BigTable.
• Work with GCP databases such as Bigtable, Spanner, CloudSQL, AlloyDB, ensuring performance, security, and availability.
• Develop and manage data processing workflows using Apache Spark, Hadoop, Hive, Kafka, and other Big Data technologies.
• Ensure data governance and security using Dataplex, Data Catalog, and other GCP governance tooling.
• Collaborate with DevOps teams to build CI/CD pipelines for data workloads using Cloud Build, Artifact Registry, and Terraform.
• Optimize query performance and data storage across structured and unstructured datasets.
• Design and implement streaming data solutions using Pub/Sub, Kafka, or equivalent technologies.
Required Skills & Qualifications:
• 8-15 years of experience
• Strong expertise in GCP Dataflow, Pub/Sub, Cloud Composer, Cloud Workflow, BigQuery, Cloud Run, Cloud Build.
• Proficiency in Python and Java, with hands-on experience in data processing and ETL pipelines.
• In-depth knowledge of relational databases (SQL, MySQL, PostgreSQL, Oracle) and NoSQL databases (MongoDB, Scylla, Cassandra, DynamoDB).
• Experience with Big Data platforms such as Cloudera, Hortonworks, MapR, Azure HDInsight, IBM Open Platform.
• Strong understanding of AWS Data services such as Redshift, RDS, Athena, SQS/Kinesis.
• Familiarity with data formats such as Avro, ORC, Parquet.
• Experience handling large-scale data migrations and implementing data lake architectures.
• Expertise in data modeling, data warehousing, and distributed data processing frameworks.
• Deep understanding of data formats such as Avro, ORC, Parquet.
• Certification in GCP Data Engineering Certification or equivalent.
Good to Have:
• Experience in BigQuery, Presto, or equivalent.
• Exposure to Hadoop, Spark, Oozie, HBase.
• Understanding of cloud database migration strategies.
• Knowledge of GCP data governance and security best practices.
Job Description -
Position: Senior Data Engineer (Azure)
Experience - 6+ Years
Mode - Hybrid
Location - Gurgaon, Pune, Jaipur, Bangalore, Bhopal
Key Responsibilities:
- Data Processing on Azure: Azure Data Factory, Streaming Analytics, Event Hubs, Azure Databricks, Data Migration Service, Data Pipeline.
- Provisioning, configuring, and developing Azure solutions (ADB, ADF, ADW, etc.).
- Design and implement scalable data models and migration strategies.
- Work on distributed big data batch or streaming pipelines (Kafka or similar).
- Develop data integration and transformation solutions for structured and unstructured data.
- Collaborate with cross-functional teams for performance tuning and optimization.
- Monitor data workflows and ensure compliance with data governance and quality standards.
- Contribute to continuous improvement through automation and DevOps practices.
Required Skills & Experience:
- 6–10 years of experience as a Data Engineer.
- Strong proficiency in Azure Databricks, PySpark, Python, SQL, and Azure Data Factory.
- Experience in Data Modelling, Data Migration, and Data Warehousing.
- Good understanding of database structure principles and schema design.
- Hands-on experience using MS SQL Server, Oracle, or similar RDBMS platforms.
- Experience in DevOps tools (Azure DevOps, Jenkins, Airflow, Azure Monitor) – good to have.
- Knowledge of distributed data processing and real-time streaming (Kafka/Event Hub).
- Familiarity with visualization tools like Power BI or Tableau.
- Strong analytical, problem-solving, and debugging skills.
- Self-motivated, detail-oriented, and capable of managing priorities effectively.
Role Summary
We’re seeking a seasoned Azure Data Engineer / Consultant to lead design, build, and operationalize cloud-native data solutions. You’ll partner with external clients—from discovery through Go-Live—to ingest, model, transform, and serve high-volume data using Synapse, Fabric, PySpark, and SQL. You’ll also establish best practices around CI/CD, security, and data quality within a medallion architecture.
Required Skills (at least 4+ years of relevant experience - this is a senior-level role)
- Ability to talk to the customer
- Manage the delivery of an End-To-End Enterprise project
- Fabric (or Synapse/ADF/Databricks) Data Engineering background
- Data Warehousing experience
- Basic understanding of Agentic AI
Preferred Skills & Certifications:
- DP-600, DP-700 or equivalent certification.
- Experience with Azure Purview, Data Catalogs, or metadata management tools.
- Familiarity with orchestration frameworks (ADF, Synapse Pipelines), Spark optimization (broadcast joins, partition pruning), and data-quality frameworks (Great Expectations, custom).
- Prior consulting or client-facing engagements in enterprise environments.
- Knowledge of BI tools (Power BI).
What We Offer:
- Opportunity to own and shape cutting-edge data solutions for diverse industries.
- Collaborative, outcome-driven culture with career growth and skill-building opportunities.
- Flexible hours and remote-first work model.
- Competitive compensation and benefits package.
At Loyalty Juggernaut, we’re on a mission to revolutionize customer loyalty through AI-driven SaaS solutions. We are THE JUGGERNAUTS, driving innovation and impact in the loyalty ecosystem with GRAVTY®, our SaaS Product that empowers multinational enterprises to build deeper customer connections. Designed for scalability and personalization, GRAVTY® delivers cutting-edge loyalty solutions that transform customer engagement across diverse industries including Airlines, Airport, Retail, Hospitality, Banking, F&B, Telecom, Insurance and Ecosystem.
Our Impact:
- 400+ million members connected through our platform.
- Trusted by 100+ global brands/partners, driving loyalty and brand devotion worldwide.
Proud to be a Three-Time Champion for Best Technology Innovation in Loyalty!!
Explore more about us at www.lji.io.
What you will OWN:
- Build the infrastructure required for optimal extraction, transformation, and loading of data from various sources using SQL and AWS ‘big data’ technologies.
- Create and maintain optimal data pipeline architecture.
- Identify, design, and implement internal process improvements, automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Work with stakeholders, including the Technical Architects, Developers, Product Owners, and Executives, to assist with data-related technical issues and support their data infrastructure needs.
- Create tools for data management and data analytics that can assist them in building and optimizing our product to become an innovative industry leader.
You would make a GREAT FIT if you have:
- Have 2 to 5 years of relevant backend development experience, with solid expertise in Python.
- Possess strong skills in Data Structures and Algorithms, and can write optimized, maintainable code.
- Are familiar with database systems, and can comfortably work with PostgreSQL, as well as NoSQL solutions like MongoDB or DynamoDB.
- Hands-on experience using Cloud Dataware houses like AWS Redshift, GBQ, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift, and AWS Batch would be an added advantage.
- Have a solid understanding of ETL processes and tools and can build or modify ETL pipelines effectively.
- Have experience managing or building data pipelines and architectures at scale.
- Understand the nuances of data ingestion, transformation, storage, and analytics workflows.
- Communicate clearly and work collaboratively across engineering, product.
Why Choose US?
- This opportunity offers a dynamic and supportive work environment where you'll have the chance to not just collaborate with talented technocrats but also work with globally recognized brands, gain exposure, and carve your own career path.
- You will get to innovate and dabble in the future of technology -Enterprise Cloud Computing, Blockchain, Machine Learning, AI, Mobile, Digital Wallets, and much more.
Job Title: Senior Data Engineer
No. of Positions: 3
Employment Type: Full-Time, Permanent
Location: Remote (Pan India)
Shift Timings: 10:00 AM – 7:00 PM IST
Experience Required: Minimum 3+ Years
Mandatory Skills: Scala & PySpark
Role Overview
We are looking for an experienced Senior Data Engineer to design, build, and optimize scalable data pipelines and architectures. The ideal candidate should have hands-on experience working with Big Data technologies, distributed systems, and ETL pipelines. You will work closely with cross-functional teams including Data Analysts, Data Scientists, and Software Engineers to ensure efficient data flow and reliable data infrastructure.
Key Responsibilities
- Design and build scalable data pipelines for extraction, transformation, and loading (ETL) from various data sources.
- Enhance internal processes by automating tasks, optimizing data workflows, and improving infrastructure performance.
- Collaborate with Product, Engineering, Data, and Business teams to understand data needs and provide solutions.
- Work closely with machine learning and analytics teams to support advanced data modeling and innovation.
- Ensure systems are highly reliable, maintainable, and optimized for performance.
Required Qualifications & Skills
- Bachelor’s degree in Computer Science, Engineering, or related field.
- 3+ years of hands-on experience in Data Engineering.
- Strong experience with Apache Spark, with solid understanding of distributed data processing.
- Proficiency in Scala and PySpark is mandatory.
- Strong SQL skills and experience working with relational and non-relational data.
- Experience with cloud-based data platforms (preferably Databricks).
- Good understanding of Delta Lake architecture, Parquet, JSON, CSV, and related data file formats.
- Comfortable working in Linux/macOS environments with scripting capabilities.
- Ability to work in an Agile environment and deliver independently.
- Good communication and collaboration skills.
- Knowledge of Machine Learning concepts is an added advantage.
Reporting
- This role will report to the CEO or a designated Team Lead.
Benefits & Work Environment
- Remote work flexibility across India.
- Encouraging and diverse work culture.
- Paid leaves, holidays, performance incentives, and learning opportunities.
- Supportive environment that promotes personal and professional growth.
MANDATORY:
- Super Quality Data Architect, Data Engineering Manager / Director Profile
- Must have 12+ YOE in Data Engineering roles, with at least 2+ years in a Leadership role
- Must have 7+ YOE in hands-on Tech development with Java (Highly preferred) or Python, Node.JS, GoLang
- Must have strong experience in large data technologies, tools like HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto etc.
- Strong expertise in HLD and LLD, to design scalable, maintainable data architectures.
- Must have managed a team of at least 5+ Data Engineers (Read Leadership role in CV)
- Product Companies (Prefers high-scale, data-heavy companies)
PREFERRED:
- Must be from Tier - 1 Colleges, preferred IIT
- Candidates must have spent a minimum 3 yrs in each company.
- Must have recent 4+ YOE with high-growth Product startups, and should have implemented Data Engineering systems from an early stage in the Company
ROLES & RESPONSIBILITIES:
- Lead and mentor a team of data engineers, ensuring high performance and career growth.
- Architect and optimize scalable data infrastructure, ensuring high availability and reliability.
- Drive the development and implementation of data governance frameworks and best practices.
- Work closely with cross-functional teams to define and execute a data roadmap.
- Optimize data processing workflows for performance and cost efficiency.
- Ensure data security, compliance, and quality across all data platforms.
- Foster a culture of innovation and technical excellence within the data team.
IDEAL CANDIDATE:
- 10+ years of experience in software/data engineering, with at least 3+ years in a leadership role.
- Expertise in backend development with programming languages such as Java, PHP, Python, Node.JS, GoLang, JavaScript, HTML, and CSS.
- Proficiency in SQL, Python, and Scala for data processing and analytics.
- Strong understanding of cloud platforms (AWS, GCP, or Azure) and their data services.
- Strong foundation and expertise in HLD and LLD, as well as design patterns, preferably using Spring Boot or Google Guice
- Experience in big data technologies such as Spark, Hadoop, Kafka, and distributed computing frameworks.
- Hands-on experience with data warehousing solutions such as Snowflake, Redshift, or BigQuery
- Deep knowledge of data governance, security, and compliance (GDPR, SOC2, etc.).
- Experience in NoSQL databases like Redis, Cassandra, MongoDB, and TiDB.
- Familiarity with automation and DevOps tools like Jenkins, Ansible, Docker, Kubernetes, Chef, Grafana, and ELK.
- Proven ability to drive technical strategy and align it with business objectives.
- Strong leadership, communication, and stakeholder management skills.
PREFERRED QUALIFICATIONS:
- Experience in machine learning infrastructure or MLOps is a plus.
- Exposure to real-time data processing and analytics.
- Interest in data structures, algorithm analysis and design, multicore programming, and scalable architecture.
- Prior experience in a SaaS or high-growth tech company.
Required Skills:
· 8+ years of being a practitioner in data engineering or a related field.
· Proficiency in programming skills in Python
· Experience with data processing frameworks like Apache Spark or Hadoop.
· Experience working on Databricks.
· Familiarity with cloud platforms (AWS, Azure) and their data services.
· Experience with data warehousing concepts and technologies.
· Experience with message queues and streaming platforms (e.g., Kafka).
· Excellent communication and collaboration skills.
· Ability to work independently and as part of a geographically distributed team.
Wissen Technology is hiring for Data Engineer
About Wissen Technology: At Wissen Technology, we deliver niche, custom-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset—ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this? Through a combination of deep domain knowledge, cutting-edge technology expertise, and a relentless focus on quality. We don’t just meet expectations—we exceed them by ensuring faster time-to-market, reduced rework, and greater alignment with client objectives. We have a proven track record of building mission-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome-based projects ensure predictable costs and timelines, while our agile pods provide clients the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top-tier talent. Our mission is clear: to be the partner of choice for building world-class custom products that deliver exceptional impact—the first time, every time.
Job Summary: Wissen Technology is hiring a Data Engineer with expertise in Python, Pandas, Airflow, and Azure Cloud Services. The ideal candidate will have strong communication skills and experience with Kubernetes.
Experience: 4-7 years
Notice Period: Immediate- 15 days
Location: Pune, Mumbai, Bangalore
Mode of Work: Hybrid
Key Responsibilities:
- Develop and maintain data pipelines using Python and Pandas.
- Implement and manage workflows using Airflow.
- Utilize Azure Cloud Services for data storage and processing.
- Collaborate with cross-functional teams to understand data requirements and deliver solutions.
- Ensure data quality and integrity throughout the data lifecycle.
- Optimize and scale data infrastructure to meet business needs.
Qualifications and Required Skills:
- Proficiency in Python (Must Have).
- Strong experience with Pandas (Must Have).
- Expertise in Airflow (Must Have).
- Experience with Azure Cloud Services.
- Good communication skills.
Good to Have Skills:
- Experience with Pyspark.
- Knowledge of Kubernetes.
Wissen Sites:
- Website: http://www.wissen.com
- LinkedIn: https://www.linkedin.com/company/wissen-technology
- Wissen Leadership: https://www.wissen.com/company/leadership-team/
- Wissen Live: https://www.linkedin.com/company/wissen-technology/posts/feedView=All
- Wissen Thought Leadership: https://www.wissen.com/articles/
Experience - 7+Yrs
Must-Have:
o Python (Pandas, PySpark)
o Data engineering & workflow optimization
o Delta Tables, Parquet
· Good-to-Have:
o Databricks
o Apache Spark, DBT, Airflow
o Advanced Pandas optimizations
o PyTest/DBT testing frameworks
Interested candidates can revert back with detail below.
Total Experience -
Relevant Experience in Python,Pandas.DE,Workflow optimization,delta table.-
Current CTC -
Expected CTC -
Notice Period -LWD -
Current location -
Desired location -
Wissen Technology is hiring for Data Engineer
About Wissen Technology:At Wissen Technology, we deliver niche, custom-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset—ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this? Through a combination of deep domain knowledge, cutting-edge technology expertise, and a relentless focus on quality. We don’t just meet expectations—we exceed them by ensuring faster time-to-market, reduced rework, and greater alignment with client objectives. We have a proven track record of building mission-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome-based projects ensure predictable costs and timelines, while our agile pods provide clients the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top-tier talent. Our mission is clear: to be the partner of choice for building world-class custom products that deliver exceptional impact—the first time, every time.
Job Summary:Wissen Technology is hiring a Data Engineer with a strong background in Python, data engineering, and workflow optimization. The ideal candidate will have experience with Delta Tables, Parquet, and be proficient in Pandas and PySpark.
Experience:7+ years
Location:Pune, Mumbai, Bangalore
Mode of Work:Hybrid
Key Responsibilities:
- Develop and maintain data pipelines using Python (Pandas, PySpark).
- Optimize data workflows and ensure efficient data processing.
- Work with Delta Tables and Parquet for data storage and management.
- Collaborate with cross-functional teams to understand data requirements and deliver solutions.
- Ensure data quality and integrity throughout the data lifecycle.
- Implement best practices for data engineering and workflow optimization.
Qualifications and Required Skills:
- Proficiency in Python, specifically with Pandas and PySpark.
- Strong experience in data engineering and workflow optimization.
- Knowledge of Delta Tables and Parquet.
- Excellent problem-solving skills and attention to detail.
- Ability to work collaboratively in a team environment.
- Strong communication skills.
Good to Have Skills:
- Experience with Databricks.
- Knowledge of Apache Spark, DBT, and Airflow.
- Advanced Pandas optimizations.
- Familiarity with PyTest/DBT testing frameworks.
Wissen Sites:
- Website: http://www.wissen.com
- LinkedIn: https://www.linkedin.com/company/wissen-technology
- Wissen Leadership: https://www.wissen.com/company/leadership-team/
- Wissen Live: https://www.linkedin.com/company/wissen-technology/posts/feedView=All
- Wissen Thought Leadership: https://www.wissen.com/articles/
Wissen | Driving Digital Transformation
A technology consultancy that drives digital innovation by connecting strategy and execution, helping global clients to strengthen their core technology.
Now Hiring: Tableau Developer (Banking Domain) 🚀
We’re looking for a 6+ years experienced Tableau pro to design and optimize dashboards for Banking & Financial Services.
🔹 Design & optimize interactive Tableau dashboards for large banking datasets
🔹 Translate KPIs into scalable reporting solutions
🔹 Ensure compliance with regulations like KYC, AML, Basel III, PCI-DSS
🔹 Collaborate with business analysts, data engineers, and banking experts
🔹 Bring deep knowledge of SQL, data modeling, and performance optimization
🌍 Location: Remote
📊 Domain Expertise: Banking / Financial Services
✨ Preferred experience with cloud data platforms (AWS, Azure, GCP) & certifications in Tableau are a big plus!
Bring your data visualization skills to transform banking intelligence & compliance reporting.
Data Engineer
Experience: 4–6 years
Key Responsibilities
- Design, build, and maintain scalable data pipelines and workflows.
- Manage and optimize cloud-native data platforms on Azure with Databricks and Apache Spark (1–2 years).
- Implement CI/CD workflows and monitor data pipelines for performance, reliability, and accuracy.
- Work with relational databases (Sybase, DB2, Snowflake, PostgreSQL, SQL Server) and ensure efficient SQL query performance.
- Apply data warehousing concepts including dimensional modelling, star schema, data vault modelling, Kimball and Inmon methodologies, and data lake design.
- Develop and maintain ETL/ELT pipelines using open-source frameworks such as Apache Spark and Apache Airflow.
- Integrate and process data streams from message queues and streaming platforms (Kafka, RabbitMQ).
- Collaborate with cross-functional teams in a geographically distributed setup.
- Leverage Jupyter notebooks for data exploration, analysis, and visualization.
Required Skills
- 4+ years of experience in data engineering or a related field.
- Strong programming skills in Python with experience in Pandas, NumPy, Flask.
- Hands-on experience with pipeline monitoring and CI/CD workflows.
- Proficiency in SQL and relational databases.
- Familiarity with Git for version control.
- Strong communication and collaboration skills with ability to work independently.
Job Title: Data Engineering Support Engineer / Manager
Experience range:-8+ Years
Location:- Mumbai
Experience :
Knowledge, Skills and Abilities
- Python, SQL
- Familiarity with data engineering
- Experience with AWS data and analytics services or similar cloud vendor services
- Strong problem solving and communication skills
- Ablity to organise and prioritise work effectively
Key Responsibilities
- Incident and user management for data and analytics platform
- Development and maintenance of Data Quliaty framework (including anomaly detection)
- Implemenation of Python & SQL hotfixes and working with data engineers on more complex issues
- Diagnostic tools implementation and automation of operational processes
Key Relationships
- Work closely with data scientists, data engineers, and platform engineers in a highly commercial environment
- Support research analysts and traders with issue resolution
Overview
We are seeking an Azure Solutions Lead who will be responsible for managing and maintaining the overall architecture, design, application management and migrations, security of growing Cloud Infrastructure that supports the company’s core business and infrastructure systems and services. In this role, you will protect our critical information, systems, and assets, build new solutions, implement, and configure new applications and hardware, provide training, and optimize/monitor cloud systems. You must be passionate about applying technical skills that create operational efficiencies and offer solutions to support business operations and strategy roadmap.
Responsibilities:
- Works in tandem with our Architecture, Applications and Security teams
- Identify and implement the most optimal and secure Azure cloud-based solutions for the company.
- Design and implement end-to-end Azure data solutions, including data ingestion, storage, processing, and visualization.
- Architect data platforms using Azure services such as Azure Data Fabric, Azure Data Factory (ADF), Azure Databricks (ADB), Azure SQL Database, and One Lake etc.
- Develop and maintain data pipelines for efficient data movement and transformation.
- Design data models and schemas to support business requirements and analytical insights.
- Collaborate with stakeholders to understand business needs and translate them into technical solutions.
- Provide technical leadership and guidance to the data engineering team.
- Stay updated on emerging Azure technologies and best practices in data architecture.
- Stay current with industry trends, making recommendations as available to help keep the environment operating at it optimum while minimizing waste and maximizing investment.
- Create and update the documentation to facilitate cross-training and troubleshooting
- Work with the Security and Architecture teams to refine and deploy security best practices to identify, detect, protect, respond, and recover from threats to assets and information.
Qualifications:
- Overall 7+ years of IT Experience & minimum 2 years as an Azure Data Lead
- Strong expertise in all aspects of Azure services with a focus on data engineering & BI reporting.
- Proficiency in Azure Data Factory (ADF), Data Factory, Azure Databricks (ADB), SQL, NoSQL, PySpark, Power BI and other Azure data tools.
- Experience in data modelling, data warehousing, and business intelligence concepts.
- Proven track record of designing and implementing scalable and robust data solutions.
- Excellent communication skills with strong teamwork, analytical and troubleshooting skills, and attentiveness to detail.
- Self-starter, ability to work independently and within a team.
NOTE: IT IS MANDATORY TO GIVE ONE TECHNICHAL ROUND FACE TO FACE.
What You’ll Be Doing:
● Design and build parts of our data pipeline architecture for extraction, transformation, and loading of data from a wide variety of data sources using the latest Big Data technologies.
● Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
● Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
● Work with machine learning, data, and analytics experts to drive innovation, accuracy and greater functionality in our data system.
Qualifications:
● Bachelor's degree in Engineering, Computer Science, or relevant field.
● 10+ years of relevant and recent experience in a Data Engineer role. ● 5+ years recent experience with Apache Spark and solid understanding of the fundamentals.
● Deep understanding of Big Data concepts and distributed systems.
● Strong coding skills with Scala, Python, Java and/or other languages and the ability to quickly switch between them with ease.
● Advanced working SQL knowledge and experience working with a variety of relational databases such as Postgres and/or MySQL.
● Cloud Experience with DataBricks
● Experience working with data stored in many formats including Delta Tables, Parquet, CSV and JSON.
● Comfortable working in a linux shell environment and writing scripts as needed.
● Comfortable working in an Agile environment
● Machine Learning knowledge is a plus.
● Must be capable of working independently and delivering stable, efficient and reliable software.
● Excellent written and verbal communication skills in English.
● Experience supporting and working with cross-functional teams in a dynamic environment.
REPORTING: This position will report to our CEO or any other Lead as assigned by Management.
EMPLOYMENT TYPE: Full-Time,
Permanent LOCATION: Remote
SHIFT TIMINGS: 2.00 pm-11:00pm IST
Technical Architect (Databricks)
- 10+ Years Data Engineering Experience with expertise in Databricks
- 3+ years of consulting experience
- Completed Data Engineering Professional certification & required classes
- Minimum 2-3 projects delivered with hands-on experience in Databricks
- Completed Apache Spark Programming with Databricks, Data Engineering with Databricks, Optimizing Apache Spark™ on Databricks
- Experience in Spark and/or Hadoop, Flink, Presto, other popular big data engines
- Familiarity with Databricks multi-hop pipeline architecture
Sr. Data Engineer (Databricks)
- 5+ Years Data Engineering Experience with expertise in Databricks
- Completed Data Engineering Associate certification & required classes
- Minimum 1 project delivered with hands-on experience in development on Databricks
- Completed Apache Spark Programming with Databricks, Data Engineering with Databricks, Optimizing Apache Spark™ on Databricks
- SQL delivery experience, and familiarity with Bigquery, Synapse or Redshift
- Proficient in Python, knowledge of additional databricks programming languages (Scala)
We’re Hiring: Senior Data Engineer | Remote (Pan India)
Are you passionate about building scalable data pipelines and optimizing data architecture? We’re looking for an experienced Senior Data Engineer (10+ years) to join our team and play a key role in shaping next-gen data systems.
What you’ll do:
✅ Design & develop robust data pipelines (ETL) using the latest Big Data tech
✅ Optimize infrastructure & automate processes for scalability
✅ Collaborate with cross-functional teams (Product, Data, Design, ML)
✅ Work with modern tools: Apache Spark, Databricks, SQL, Python/Scala/Java
Scala is mandatory
What we’re looking for:
🔹 Strong expertise in Big Data, Spark & distributed systems
🔹 Hands-on with SQL, relational DBs (Postgres/MySQL), Linux scripting
🔹 Experience with Delta Tables, Parquet, CSV, JSON
🔹 Cloud & Databricks exposure
🔹 Bonus: Machine Learning knowledge
📍 Location: Remote (Pan India)
⏰ Shift: 2:00 pm – 11:00 pm IST
💼 Type: Full-time, Permanent
Job Title: Lead Data Engineer
📍 Location: Pune
🧾 Experience: 10+ Years
💰 Budget: Up to 1.7 LPM
Responsibilities
- Collaborate with Data & ETL teams to review, optimize, and scale data architectures within Snowflake.
- Design, develop, and maintain efficient ETL/ELT pipelines and robust data models.
- Optimize SQL queries for performance and cost efficiency.
- Ensure data quality, reliability, and security across pipelines and datasets.
- Implement Snowflake best practices for performance, scaling, and governance.
- Participate in code reviews, knowledge sharing, and mentoring within the data engineering team.
- Support BI and analytics initiatives by enabling high-quality, well-modeled datasets.
Exp: 10+ Years
CTC: 1.7 LPM
Location: Pune
SnowFlake Expertise Profile
Should hold 10 + years of experience with strong skills with core understanding of cloud data warehouse principles and extensive experience in designing, building, optimizing, and maintaining robust and scalable data solutions on the Snowflake platform.
Possesses a strong background in data modelling, ETL/ELT, SQL development, performance tuning, scaling, monitoring and security handling.
Responsibilities:
* Collaboration with Data and ETL team to review code, understand current architecture and help improve it based on Snowflake offerings and experience
* Review and implement best practices to design, develop, maintain, scale, efficiently monitor data pipelines and data models on the Snowflake platform for
ETL or BI.
* Optimize complex SQL queries for data extraction, transformation, and loading within Snowflake.
* Ensure data quality, integrity, and security within the Snowflake environment.
* Participate in code reviews and contribute to the team's development standards.
Education:
* Bachelor’s degree in computer science, Data Science, Information Technology, or anything equivalent.
* Relevant Snowflake certifications are a plus (e.g., Snowflake certified Pro / Architecture / Advanced).
Notice Period - 0-15 days Max
Apply only who are currently in Karnataka
F2F interview
Interview - 4 rounds
Job Title: AI Specialist
Company Overview: We are the Technology Center of Excellence for Long Arc Capital
which provides growth capital to businesses with a sustainable competitive advantage and
a strong management team with whom we can partner to build a category leader. We focus
on North American and European companies where technology is transforming traditional
business models in the Financial Services, Business Services, Technology, Media and
Telecommunications sectors.
As part of our mission to leverage AI for business innovation, we are establishing AI COE to
develop Generative AI (GenAI) and Agentic AI solutions that enhance decision-making,
automation, and user experiences.
Job Overview: We are seeking dynamic and talented individuals to join our AI COE. This
team will focus on developing advanced AI models, integrating them into our cloud-based
platform, and delivering impactful solutions that drive efficiency, innovation, and customer
value.
Key Responsibilities:
• As a Full Stack AI Engineer, research, design, and develop AI solutions for text,
image, audio, and video generation
• Build and deploy Agentic AI systems for autonomous decision-making across
business outcomes and enhancing associate productivity.
• Work with domain experts to design and fine-tune AI solutions tailored to portfoliospecific challenges.
• Partner with data engineers across portfolio companies to –
o Preprocess large datasets and ensure high-quality input for training AI
models.
o Develop scalable and efficient AI pipelines using frameworks like
TensorFlow, PyTorch, and Hugging Face.
• Implement MLOps best practices for AI model deployment, versioning, and
monitoring using tools like MLflow and Kubernetes.
• Ensure AI solutions adhere to ethical standards, comply with regulations (e.g.,
GDPR, CCPA), and mitigate biases.
• Design intuitive and user-friendly interfaces for AI-driven applications, collaborating
with UX designers and frontend developers.
Internal Use Only
• Stay up to date with the latest AI research and tools and evaluate their applicability
to our business needs.
Key Qualifications:
Technical Expertise:
• Proficiency in full stack application development (specifically using Angular, React).
• Expertise in backend technologies (Django, Flask) and cloud platforms (AWS
SageMaker/Azure AI Studio).
• Proficiency in deep learning frameworks (TensorFlow, PyTorch, JAX).
• Proficiency with Large Language Models (LLMs) and generative AI tools (e.g., OpenAI
APIs, LangChain, Stable Diffusion).
• Solid understanding of data engineering workflows, including ETL processes and
distributed computing tools (Apache Spark, Kafka).
• Experience with data pipelines, big data processing, and database management
(SQL, NoSQL).
• Knowledge of containerization (Docker) and orchestration (Kubernetes) for scalable
AI deployment.
• Familiarity with CI/CD pipelines and automation tools (Terraform, Jenkins).
• Good understanding of AI ethics, bias mitigation, and compliance standards.
• Excellent problem-solving abilities and innovative thinking.
• Strong collaboration and communication skills, with the ability to work in crossfunctional teams.
• Proven ability to work in a fast-paced and dynamic environment.
Preferred Qualifications:
• Advanced studies in Artificial Intelligence, or a related field.
• Experience with reinforcement learning, multi-agent systems, or autonomous
decision-making
1. Design, develop, and maintain data pipelines using Azure Data Factory
2. Create and manage data models in PostgreSQL, ensuring efficient data storage and retrieval.
3. Optimize query performance and database performance in PostgreSQL, including indexing, query tuning, and performance monitoring.
4. Strong knowledge on data modeling and mapping from various sources to data model.
5. Develop and maintain logging mechanisms in Azure Data Factory to monitor and troubleshoot data pipelines.
6. Strong knowledge on Key Vault, Azure Data lake, PostgreSQL
7. Manage file handling within Azure Data Factory, including reading, writing, and transforming data from various file formats.
8. Strong SQL query skills with the ability to handle multiple scenarios and optimize query performance.
9. Excellent problem-solving skills and ability to handle complex data scenarios.
10. Collaborate with Business stakeholder, data architects and PO's to understand and meet their data requirements.
11. Ensure data quality and integrity through validation and quality checks.
12. Having Power BI knowledge, creating and configuring semantic models & reports would be preferred.
Duties
- Perform site survey and analysis on all noise and vibration requirement
- Develop acoustic system design concepts and report to achieve project and product performance requirements
- Troubleshoot noise issue and provide solution
- Collaborate with the sale team to provide acoustic solution through site visits and measurement
- Study Project specification and propose suitable product and solution
- Prepare project BOQ and Technical submittal
- Develop and improve the company acoustic products
Experience
- Good knowledge and understanding of acoustic testing and measurement techniques
- Good experience in Acoustic Software's
- Good Experience in AutoCAD and other modelling software
Key Responsibilities
● Design & Development
○ Architect and implement data ingestion pipelines using Microsoft Fabric Data Factory (Dataflows) and OneLake sources
○ Build and optimize Lakehouse and Warehouse solutions leveraging Delta Lake, Spark Notebooks, and SQL Endpoints
○ Define and enforce Medallion (Bronze–Silver–Gold) architecture patterns for raw, enriched, and curated datasets
● Data Modeling & Transformation
○ Develop scalable transformation logic in Spark (PySpark/Scala) and Fabric SQL to support reporting and analytics
○ Implement slowly changing dimensions (SCD Type 2), change-data-capture (CDC) feeds, and time-windowed aggregations
● Performance Tuning & Optimization
○ Monitor and optimize data pipelines for throughput, cost efficiency, and reliability
○ Apply partitioning, indexing, caching, and parallelism best practices in Fabric Lakehouses and Warehouse compute
● Data Quality & Governance
○ Integrate Microsoft Purview for metadata cataloging, lineage tracking, and data discovery
○ Develop automated quality checks, anomaly detection rules, and alerts for data reliability
● CI/CD & Automation
○ Implement infrastructure-as-code (ARM templates or Terraform) for Fabric workspaces, pipelines, and artifacts
○ Set up Git-based version control, CI/CD pipelines (e.g. Azure DevOps) for seamless deployment across environments
● Collaboration & Support
○ Partner with data scientists, BI developers, and business analysts to understand requirements and deliver data solutions
○ Provide production support, troubleshoot pipeline failures, and drive root-cause analysis
Required Qualifications
● 5+ years of professional experience in data engineering roles, with at least 1 year working hands-on in Microsoft Fabric
● Strong proficiency in:
○ Languages: SQL (T-SQL), Python, and/or Scala
○ Fabric Components: Data Factory Dataflows, OneLake, Spark Notebooks, Lakehouse, Warehouse
○ Data Storage: Delta Lake, Parquet, CSV, JSON formats
● Deep understanding of data modeling principles (star schemas, snowflake schemas, normalized vs. denormalized)
● Experience with CI/CD and infrastructure-as-code for data platforms (ARM templates, Terraform, Git)
● Familiarity with data governance tools, especially Microsoft Purview
● Excellent problem-solving skills and ability to communicate complex technical concepts clearly
NOTE: Candidate should be willing to take one technical round F2F from any of the branch location. (Pune/ Mumbai/ Bangalore)
∙
Good experience in 5+ SQL and NoSQL database development and optimization.
∙Strong hands-on experience with Amazon Redshift, MySQL, MongoDB, and Flyway.
∙In-depth understanding of data warehousing principles and performance tuning techniques.
∙Strong hands-on experience in building complex aggregation pipelines in NoSQL databases such as MongoDB.
∙Proficient in Python or Scala for data processing and automation.
∙3+ years of experience working with AWS-managed database services.
∙3+ years of experience with Power BI or similar BI/reporting platforms.
Job Title : Data Engineer – GCP + Spark + DBT
Location : Bengaluru (On-site at Client Location | 3 Days WFO)
Experience : 8 to 12 Years
Level : Associate Architect
Type : Full-time
Job Overview :
We are looking for a seasoned Data Engineer to join the Data Platform Engineering team supporting a Unified Data Platform (UDP). This role requires hands-on expertise in DBT, GCP, BigQuery, and PySpark, with a solid foundation in CI/CD, data pipeline optimization, and agile delivery.
Mandatory Skills : GCP, DBT, Google Dataform, BigQuery, PySpark/Spark SQL, Advanced SQL, CI/CD, Git, Agile Methodologies.
Key Responsibilities :
- Design, build, and optimize scalable data pipelines using BigQuery, DBT, and PySpark.
- Leverage GCP-native services like Cloud Storage, Pub/Sub, Dataproc, Cloud Functions, and Composer for ETL/ELT workflows.
- Implement and maintain CI/CD for data engineering projects with Git-based version control.
- Collaborate with cross-functional teams including Infra, Security, and DataOps for reliable, secure, and high-quality data delivery.
- Lead code reviews, mentor junior engineers, and enforce best practices in data engineering.
- Participate in Agile sprints, backlog grooming, and Jira-based project tracking.
Must-Have Skills :
- Strong experience with DBT, Google Dataform, and BigQuery
- Hands-on expertise with PySpark/Spark SQL
- Proficient in GCP for data engineering workflows
- Solid knowledge of SQL optimization, Git, and CI/CD pipelines
- Agile team experience and strong problem-solving abilities
Nice-to-Have Skills :
- Familiarity with Databricks, Delta Lake, or Kafka
- Exposure to data observability and quality frameworks (e.g., Great Expectations, Soda)
- Knowledge of MDM patterns, Terraform, or IaC is a plus
Job Title : AI Architect
Location : Pune (On-site | 3 Days WFO)
Experience : 6+ Years
Shift : US or flexible shifts
Job Summary :
We are looking for an experienced AI Architect to design and deploy AI/ML solutions that align with business goals.
The role involves leading end-to-end architecture, model development, deployment, and integration using modern AI/ML tools and cloud platforms (AWS/Azure/GCP).
Key Responsibilities :
- Define AI strategy and identify business use cases
- Design scalable AI/ML architectures
- Collaborate on data preparation, model development & deployment
- Ensure data quality, governance, and ethical AI practices
- Integrate AI into existing systems and monitor performance
Must-Have Skills :
- Machine Learning, Deep Learning, NLP, Computer Vision
- Data Engineering, Model Deployment (CI/CD, MLOps)
- Python Programming, Cloud (AWS/Azure/GCP)
- Distributed Systems, Data Governance
- Strong communication & stakeholder collaboration
Good to Have :
- AI certifications (Azure/GCP/AWS)
- Experience in big data and analytics
Job Title : Senior Data Engineer
Experience : 6 to 10 Years
Location : Gurgaon (Hybrid – 3 days office / 2 days WFH)
Notice Period : Immediate to 30 days (Buyout option available)
About the Role :
We are looking for an experienced Senior Data Engineer to join our Digital IT team in Gurgaon.
This role involves building scalable data pipelines, managing data architecture, and ensuring smooth data flow across the organization while maintaining high standards of security and compliance.
Mandatory Skills :
Azure Data Factory (ADF), Azure Cloud Services, SQL, Data Modelling, CI/CD tools, Git, Data Governance, RDBMS & NoSQL databases (e.g., SQL Server, PostgreSQL, Redis, ElasticSearch), Data Lake migration.
Key Responsibilities :
- Design and develop secure, scalable end-to-end data pipelines using Azure Data Factory (ADF) and Azure services.
- Build and optimize data architectures (including Medallion Architecture).
- Collaborate with cross-functional teams on cybersecurity, data privacy (e.g., GDPR), and governance.
- Manage structured/unstructured data migration to Data Lake.
- Ensure CI/CD integration for data workflows and version control using Git.
- Identify and integrate data sources (internal/external) in line with business needs.
- Proactively highlight gaps and risks related to data compliance and integrity.
Required Skills :
- Azure Data Factory (ADF) – Mandatory
- Strong SQL and Data Modelling expertise.
- Hands-on with Azure Cloud Services and data architecture.
- Experience with CI/CD tools and version control (Git).
- Good understanding of Data Governance practices.
- Exposure to ETL/ELT pipelines and Data Lake migration.
- Working knowledge of RDBMS and NoSQL databases (e.g., SQL Server, PostgreSQL, Redis, ElasticSearch).
- Understanding of RESTful APIs, deployment on cloud/on-prem infrastructure.
- Strong problem-solving, communication, and collaboration skills.
Additional Info :
- Work Mode : Hybrid (No remote); relocation to Gurgaon required for non-NCR candidates.
- Communication : Above-average verbal and written English skills.
Perks & Benefits :
- 5 Days work week
- Global exposure and leadership collaboration.
- Health insurance, employee-friendly policies, training and development.
Role Overview:
We are seeking a Senior Software Engineer (SSE) with strong expertise in Kafka, Python, and Azure Databricks to lead and contribute to our healthcare data engineering initiatives. This role is pivotal in building scalable, real-time data pipelines and processing large-scale healthcare datasets in a secure and compliant cloud environment.
The ideal candidate will have a solid background in real-time streaming, big data processing, and cloud platforms, along with strong leadership and stakeholder engagement capabilities.
Key Responsibilities:
- Design and develop scalable real-time data streaming solutions using Apache Kafka and Python.
- Architect and implement ETL/ELT pipelines using Azure Databricks for both structured and unstructured healthcare data.
- Optimize and maintain Kafka applications, Python scripts, and Databricks workflows to ensure performance and reliability.
- Ensure data integrity, security, and compliance with healthcare standards such as HIPAA and HITRUST.
- Collaborate with data scientists, analysts, and business stakeholders to gather requirements and translate them into robust data solutions.
- Mentor junior engineers, perform code reviews, and promote engineering best practices.
- Stay current with evolving technologies in cloud, big data, and healthcare data standards.
- Contribute to the development of CI/CD pipelines and containerized environments (Docker, Kubernetes).
Required Skills & Qualifications:
- 4+ years of hands-on experience in data engineering roles.
- Strong proficiency in Kafka (including Kafka Streams, Kafka Connect, Schema Registry).
- Proficient in Python for data processing and automation.
- Experience with Azure Databricks (or readiness to ramp up quickly).
- Solid understanding of cloud platforms, with a preference for Azure (AWS/GCP is a plus).
- Strong knowledge of SQL and NoSQL databases; data modeling for large-scale systems.
- Familiarity with containerization tools like Docker and orchestration using Kubernetes.
- Exposure to CI/CD pipelines for data applications.
- Prior experience with healthcare datasets (EHR, HL7, FHIR, claims data) is highly desirable.
- Excellent problem-solving abilities and a proactive mindset.
- Strong communication and interpersonal skills to work in cross-functional teams.
Strong Data Architect, Lead Data Engineer, Engineering Manager / Director Profile
Mandatory (Experience 1) - Must have 10+ YOE in Data Engineering roles, with at least 2+ years in a Leadership role
Mandatory (Experience 2) - Must have 7+ YOE in hands-on Tech development with Java (Highly preferred) or Python, Node.JS, GoLang
Mandatory (Experience 3) - Must have recent 4+ YOE with high-growth Product startups, and should have implemented Data Engineering systems from an early stage in the Company
Mandatory (Experience 4) - Must have strong experience in large data technologies, tools like HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto etc.
Mandatory (Experience 5) - Strong expertise in HLD and LLD, to design scalable, maintainable data architectures.
Mandatory (Team Management) - Must have managed a team of atleast 5+ Data Engineers (Read Leadership role in CV)
Mandatory (Education) - Must be from Tier - 1 Colleges, preferred IIT
Mandatory (Company) - B2B Product Companies with High data-traffic
Preferred Companies
MoEngage, Whatfix, Netcore Cloud, Clevertap, Hevo Data, Snowflake, Chargebee, Fractor.ai, Databricks, Dataweave, Wingman, Postman, Zoho, HighRadius, Freshworks, Mindtickle
🛠️ Key Responsibilities
- Design, build, and maintain scalable data pipelines using Python and Apache Spark (PySpark or Scala APIs)
- Develop and optimize ETL processes for batch and real-time data ingestion
- Collaborate with data scientists, analysts, and DevOps teams to support data-driven solutions
- Ensure data quality, integrity, and governance across all stages of the data lifecycle
- Implement data validation, monitoring, and alerting mechanisms for production pipelines
- Work with cloud platforms (AWS, GCP, or Azure) and tools like Airflow, Kafka, and Delta Lake
- Participate in code reviews, performance tuning, and documentation
🎓 Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
- 3–6 years of experience in data engineering with a focus on Python and Spark
- Experience with distributed computing and handling large-scale datasets (10TB+)
- Familiarity with data security, PII handling, and compliance standards is a plus
Job Title : Python Data Engineer
Experience : 4+ Years
Location : Bangalore / Hyderabad (On-site)
Job Summary :
We are seeking a skilled Python Data Engineer to work on cloud-native data platforms and backend services.
The role involves building scalable APIs, working with diverse data systems, and deploying containerized services using modern cloud infrastructure.
Mandatory Skills : Python, AWS, RESTful APIs, Microservices, SQL/PostgreSQL/NoSQL, Docker, Kubernetes, CI/CD (Jenkins/GitLab CI/AWS CodePipeline)
Key Responsibilities :
- Design, develop, and maintain backend systems using Python.
- Build and manage RESTful APIs and microservices architectures.
- Work extensively with AWS cloud services for deployment and data storage.
- Implement and manage SQL, PostgreSQL, and NoSQL databases.
- Containerize applications using Docker and orchestrate with Kubernetes.
- Set up and maintain CI/CD pipelines using Jenkins, GitLab CI, or AWS CodePipeline.
- Collaborate with teams to ensure scalable and reliable software delivery.
- Troubleshoot and optimize application performance.
Must-Have Skills :
- 4+ years of hands-on experience in Python backend development.
- Strong experience with AWS cloud infrastructure.
- Proficiency in building microservices and APIs.
- Good knowledge of relational and NoSQL databases.
- Experience with Docker and Kubernetes.
- Familiarity with CI/CD tools and DevOps processes.
- Strong problem-solving and collaboration skills.
Job Title : Data Engineer – Snowflake Expert
Location : Pune (Onsite)
Experience : 10+ Years
Employment Type : Contractual
Mandatory Skills : Snowflake, Advanced SQL, ETL/ELT (Snowpipe, Tasks, Streams), Data Modeling, Performance Tuning, Python, Cloud (preferably Azure), Security & Data Governance.
Job Summary :
We are seeking a seasoned Data Engineer with deep expertise in Snowflake to design, build, and maintain scalable data solutions.
The ideal candidate will have a strong background in data modeling, ETL/ELT, SQL optimization, and cloud data warehousing principles, with a passion for leveraging Snowflake to drive business insights.
Responsibilities :
- Collaborate with data teams to optimize and enhance data pipelines and models on Snowflake.
- Design and implement scalable ELT pipelines with performance and cost-efficiency in mind.
- Ensure high data quality, security, and adherence to governance frameworks.
- Conduct code reviews and align development with best practices.
Qualifications :
- Bachelor’s in Computer Science, Data Science, IT, or related field.
- Snowflake certifications (Pro/Architect) preferred.
What You’ll Be Doing:
● Design and build parts of our data pipeline architecture for extraction, transformation, and loading of data from a wide variety of data sources using the latest Big Data technologies.
● Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
● Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
● Work with machine learning, data, and analytics experts to drive innovation, accuracy and greater functionality in our data system. Qualifications:
● Bachelor's degree in Engineering, Computer Science, or relevant field.
● 10+ years of relevant and recent experience in a Data Engineer role. ● 5+ years recent experience with Apache Spark and solid understanding of the fundamentals.
● Deep understanding of Big Data concepts and distributed systems.
● Strong coding skills with Scala, Python, Java and/or other languages and the ability to quickly switch between them with ease.
● Advanced working SQL knowledge and experience working with a variety of relational databases such as Postgres and/or MySQL.
● Cloud Experience with DataBricks
● Experience working with data stored in many formats including Delta Tables, Parquet, CSV and JSON.
● Comfortable working in a linux shell environment and writing scripts as needed.
● Comfortable working in an Agile environment
● Machine Learning knowledge is a plus.
● Must be capable of working independently and delivering stable, efficient and reliable software.
● Excellent written and verbal communication skills in English.
● Experience supporting and working with cross-functional teams in a dynamic environment
EMPLOYMENT TYPE: Full-Time, Permanent
LOCATION: Remote (Pan India)
SHIFT TIMINGS: 2.00 pm-11:00pm IST
Job Description: Data Engineer
Position Overview:
Role Overview
We are seeking a skilled Python Data Engineer with expertise in designing and implementing data solutions using the AWS cloud platform. The ideal candidate will be responsible for building and maintaining scalable, efficient, and secure data pipelines while leveraging Python and AWS services to enable robust data analytics and decision-making processes.
Key Responsibilities
· Design, develop, and optimize data pipelines using Python and AWS services such as Glue, Lambda, S3, EMR, Redshift, Athena, and Kinesis.
· Implement ETL/ELT processes to extract, transform, and load data from various sources into centralized repositories (e.g., data lakes or data warehouses).
· Collaborate with cross-functional teams to understand business requirements and translate them into scalable data solutions.
· Monitor, troubleshoot, and enhance data workflows for performance and cost optimization.
· Ensure data quality and consistency by implementing validation and governance practices.
· Work on data security best practices in compliance with organizational policies and regulations.
· Automate repetitive data engineering tasks using Python scripts and frameworks.
· Leverage CI/CD pipelines for deployment of data workflows on AWS.

















