Data Engineer at Ascendeum · Remote only · 1 - 3 years · ₹6L - ₹9L / yr · Profitable · Remote only · Posted 19 Jun 2023

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Understand long-term and short-term business requirements to precision match it with the capabilities of different distributed storage and computing technologies from the plethora of options available in the ecosystem.
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Create complex data processing pipelines
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Design scalable implementations of the models developed by our Data Scientist.
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Deploy data pipelines in production systems based on CICD practices
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Create and maintain clear documentation on data models/schemas as well as
transformation/validation rules
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Troubleshoot and remediate data quality issues raised by pipeline alerts or downstream consumers

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We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.
Qualifications and Skills:
- Minimum 5 years of experience as a Data Engineer
- Hands-on experience with Azure cloud-based data solutions
- Fabric experience is a must – designing, implementing, and managing data workflows and pipelines
- Expertise in database design and management, including SQL databases such as SQL Server
- Proficient in ETL (Extract, Transform, Load) design for data integration and processing
- Strong knowledge of data modeling principles and techniques
- Experience with Azure Data Factory (ADF) for orchestrating data workflows
- Ability to analyze and translate data into actionable insights, reports, and visualizations
- Proficiency in Power BI for reporting and data visualization
Desirable Skills:
- Experience with Power BI Report Builder / Reporting Services
- Knowledge of statistical analysis or Data Science
- Experience within the UK Insurance industry is a plus
- Python or R coding skills
Responsibilities:
- Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
- Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
- Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
- Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
- Implement different methods of streaming data and create reconciliations for datasets
- Build analytical models to support reporting and analytics
- Collaborate with an agile delivery team to work on the backlog of specified work
Job Title : Senior Data Engineer – Databricks
Experience : 14 to 20 Years
Location : HSR Layout, Bangalore
Work Mode : Hybrid – 3 Days WFO
Shift : 11:30 AM – 07:30 PM IST
Positions : 2
Notice Period : Immediate Joiners Only
Interview : 1 Technical Round + 2 Client Rounds
Role Overview :
We are looking for a Senior Data Engineer to build and lead enterprise-scale data platforms for a Switzerland-based commodity client.
The role requires a strong hands-on Data Engineering professional with expertise in Databricks, PySpark, Python, SQL, and AWS, along with technical leadership and stakeholder management experience.
Must-Have Skills :
- 14 to 20 years of Data Engineering experience
- Databricks & Apache Spark / PySpark
- Python & SQL
- AWS Cloud
- Lakehouse Architecture
- ETL / ELT & Distributed Data Processing
- Batch & Streaming Pipelines
- Data Pipeline Optimization & Data Modeling
- CDC & Incremental Processing
- Git, CI/CD & Testing
- Data Quality, Monitoring & Observability
- Technical Leadership & Stakeholder Management
Key Responsibilities :
- Design and build scalable data pipelines using Databricks, PySpark, Python, SQL, and AWS.
- Own data products from design through production.
- Develop batch / streaming pipelines and reusable ETL / ELT frameworks.
- Optimize pipelines for performance, scalability, reliability, and cost.
- Design scalable data architectures and data models.
- Implement data quality, monitoring, lineage, and CI/CD practices.
- Lead technical discussions and mentor engineering teams.
- Collaborate with business stakeholders, architects, product owners, and engineering teams.
- Remain hands-on while providing technical leadership.
Ideal Candidate :
A 14 to 20 years experienced, hands-on Data Engineering leader with strong Databricks + PySpark + AWS expertise, excellent communication, stakeholder management, and experience delivering enterprise-scale data platforms.
🔴 Super Urgent : Only Bangalore-based immediate joiners.
Company Name – Wissen Technology
Group of companies in India – Wissen Technology & Wissen Infotech
Work Location – Whitefield, Bangalore
Website and Company profile:
www.wissen.com
LinkedIn Page:
https://www.linkedin.com/company/wissen-technology/
While you may already know about Wissen and the company history, here is a quick rundown for you.
About Wissen Technology:
· The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015.
· Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains. We help clients build world class products.
· Our workforce has highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like Wharton, MIT, IITs, IIMs, and NITs and with rich work experience in some of the biggest companies in the world.
· Wissen Technology has grown its revenues by 400% in these five years without any external funding or investments.
· Globally present with offices US, India, UK, Australia, Mexico, and Canada.
· We offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.
· Wissen Technology has been certified as a Great Place to Work®.
· Wissen Technology has been voted as the Top 20 AI/ML vendor by CIO Insider in 2020.
· Over the years, Wissen Group has successfully delivered $650 million worth of projects for more than 20 of the Fortune 500 companies.
· We have served client across sectors like Banking, Telecom, Healthcare, Manufacturing, and Energy. They include likes of Morgan Stanley, Goldman Sachs, MSCI, StateStreet, Flipkart, Swiggy, Trafigura, GE to name a few.
About Role :
Key Responsibilities
- Build and maintain data transformation pipelines using java Spark
- Develop and optimize large-scale/CPU intensive data processing using Apache Spark
- Orchestrate workflows using Airflow
- Implement data quality checks, testing, and monitoring for pipeline. Good to have exposer into managing metadata, cataloguing, and lineage
- Support schema evolution, backfills, and incremental processing
- Ensure pipelines meet SLAs for freshness, reliability, and performance
- Expertise/working knowledge in Spark and HBase(semantic layer, virtual datasets, Reflections)
Required Skills & Qualifications
- Strong hands-on experience with
- HBase
- Apache Spark
- Experience with HBase or similar lakehouse query engines
- Airflow
- Understanding of data catalogs and lineage (e.g., OpenLineage, DataHub, Apache Polaris , openlineage)
- Proficiency in Java
- Experience with Git-based development and CI/CD
Nice-to-Have Skills
- OpenTable format/Iceberg ,Apache Arrow
- CDC-based analytics pipelines
- Cloud platforms (AWS)
- Kubernetes-based data platforms
Job Summary
Role Overview
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.
Experience with Google Cloud Platform (GCP) will be an added advantage.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
- Develop complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain reliable data integration workflows across multiple data sources.
- Perform data cleansing, validation, transformation, and quality checks.
- Analyze data and provide insights to support business and technical requirements.
- Implement and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
- Troubleshoot data pipeline failures, performance issues, and production incidents.
- Optimize data processing workflows for performance, scalability, and reliability.
- Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
- Follow best practices for version control, testing, documentation, and deployment.
- Contribute to cloud-based data engineering initiatives, preferably on GCP.
Required Skills
- 5–7 years of hands-on experience in Data Engineering.
- Strong programming skills in Python.
- Strong expertise in Advanced SQL and database concepts.
- Hands-on experience with ETL/ELT processes and data pipelines.
- Good understanding of Data Warehousing and Data Modeling concepts.
- Experience with CI/CD practices and tools.
- Strong understanding of DevOps principles, automation, and deployment processes.
- Strong data analytics and problem-solving skills.
- Experience working with large datasets and performance optimization.
- Good understanding of Git/version control and software development best practices.
Good to Have
- Hands-on experience with Google Cloud Platform (GCP).
- Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
- Experience with containerization/orchestration technologies such as Docker/Kubernetes.
- Experience with workflow orchestration tools such as Airflow.
- Knowledge of cloud-based data architecture and distributed data processing.
Preferred Candidate Profile
- Strong analytical and problem-solving abilities.
- Good communication and stakeholder management skills.
- Ability to work independently as well as in a collaborative team environment.
- Strong ownership of data pipelines and production systems.
- Candidates who can join at short notice are preferred.
Mandatory Skills
Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops
Data Engineer Short Hiring Post
🚨 Hiring: Data Engineer
🔹 Experience: 5–9 Years
🔹 Location: Bangalore / Hyderabad
🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling
🔹 Process: L1 Virtual → L2 F2F Karat Test
🔹 F2F: Bangalore / Hyderabad Location
🔹 Positions: Immediate requirement
⚠️ Note: Candidates must be available for F2F Karat immediately after L1.
#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners
Description
We are looking for Senior Data Engineers to join our AdTech team and build scalable, high-performance data platforms that power advertising insights and analytics. The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Spark and Scala.
You will work on designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL pipelines for large-scale data processing.
- Build and optimize distributed data applications using Spark and Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Work with large datasets to ensure data quality, consistency, and performance.
- Collaborate with engineering, product, and analytics teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, and cost efficiency.
- Deploy and manage data workloads in cloud and containerized environments.
- Troubleshoot production issues and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering or Big Data Engineering.
- Strong hands-on experience with Apache Spark and Scala.
- Experience building and maintaining ETL pipelines.
- Familiarity with Google Cloud Storage (GCS).
- Experience with Kubernetes (K8s).
- Strong SQL skills and understanding of distributed data processing.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with AWS and cloud-native data services.
- Familiarity with streaming technologies such as Kafka.
- Experience working on large-scale data platforms or AdTech systems.
- Exposure to orchestration tools such as Airflow.
Benefits
- Best-in-class salary: We hire strong talent and compensate accordingly.
- Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
- Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
- High-impact work: Build AI-first systems and products used at scale by global clients.
About Us
Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.
Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.
Description
We are looking for Senior Data Engineers to join our Data Platform team and build scalable, high-performance data platforms that power data processing, analytics, and downstream applications.
The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Apache Spark and Python Scala.
You will be responsible for designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL and data processing pipelines for large-scale datasets.
- Build and optimize distributed data applications using Apache Spark and Python Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Design and manage data workflows using Apache Airflow.
- Build and operate data workloads on AWS, with strong usage of Amazon S3 for large-scale data storage.
- Work with large datasets to ensure data quality, consistency, reliability, and performance.
- Collaborate with engineering, product, analytics, and other platform teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, performance, and cost efficiency.
- Troubleshoot production issues, identify bottlenecks, and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering, Big Data Engineering, or a similar role.
- Strong hands-on experience with Apache Spark and Scala.
- Experience designing, building, and maintaining large-scale ETL pipelines.
- Strong hands-on experience with AWS, particularly Amazon S3.
- Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
- Strong SQL skills and a solid understanding of distributed data processing concepts.
- Experience working with batch and/or streaming data pipelines.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with Databricks and the broader Databricks data platform.
- Familiarity with streaming technologies such as Apache Kafka.
- Experience working on large-scale data platforms handling high-volume data workloads.
- Exposure to additional AWS data services and cloud-native data architectures.
Job Description
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, SQL, CI/CD, and DevOps to design, develop, and maintain scalable data pipelines and data processing solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines.
- Develop data processing solutions using Python.
- Write complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain data ingestion and integration workflows.
- Implement data quality, validation, monitoring, and error-handling processes.
- Develop and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps tools and practices for automated build, deployment, and infrastructure management.
- Collaborate with data analysts, data scientists, software engineers, and business teams.
- Optimize data pipelines for performance, reliability, and scalability.
- Troubleshoot production data issues and ensure timely resolution.
- Follow best practices for version control, code quality, testing, and deployment.
Mandatory Skills
- Python
- ETL
- SQL
- CI/CD
- DevOps
- Git / Version Control
- Strong problem-solving and debugging skills
About Us:
The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.
Job Summary:
We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.
As a Senior Data Engineer, you will work with internal and external data, collaborate with data scientists, and contribute to the design, development, and deployment of innovative solutions.
Key Responsibilities:
- Design, develop, test, and maintain optimal data pipeline and ETL architectures.
- Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.
- Prepare and optimize data for predictive and prescriptive modeling.
- Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.
- Enhance cloud data infrastructure on AWS or Azure for scalability and performance.
- Utilize big data tools and frameworks to optimize data acquisition and preparation.
- Build architectures to move data to/from data lakes and data warehouses for advanced analytics.
- Develop and curate data models for analytics, dashboards, and reports.
- Conduct code reviews, maintain production-level code, and implement testing approaches.
- Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.
- Drive innovation and implement efficient new approaches to data engineering tasks.
Must-Have Skills:
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
- 5+ years of experience working with enterprise data platforms, including building and managing data lakes.
- 3–5 years of experience designing and implementing data warehouse solutions.
- Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
- Proficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.
- Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
- Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
- Hands-on experience with orchestration tools (e.g., Apache Airflow, Prefect).
- Knowledge of CI/CD processes, version control (e.g., Git, Jenkins), and deployment automation.
- Strong problem-solving, communication, and collaboration skills.
Good-to-Have Skills:
- Experience in integrating ERP data into data lakes.
- Experience with traditional ETL tools (e.g., Talend, Pentaho).
Competencies:
- Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
- Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
- Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
- Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
- Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.
Why Join Us?
- Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
- Work on impactful projects that make a difference across industries.
- Opportunities for professional growth and continuous learning.
- Competitive salary and benefits package.
Application Details
Ready to make an impact? Apply today and become part of the QX Impact team!
Dear Candidate,
Greeting from NAM Info Pvt Ltd.
We have a role for Data Engineer position with NAM Info.
This role will be permanent with NAM info and deploy to client
location NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA.
Work Mode: WORK FROM OFFICE
A decent hike can be provided based on current CTC
Interview Mode: Virtual
Role Descriptions:
Exp Range: 7 - 10 years
City Locations: NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA
Key Responsibilities*
Role: Data Engineer
Location: ~NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA
Skills: Digital: Databricks, Azure Data Factory
Experience Required: 8-10
Descriptions:
Good information and sound knowledge in Azure Synapse Analytics Azure Data Factory (ADF)Big Data technologies and data processing frameworks Azure Data Warehouse and associated Azure data platform services Data integration| data modelling| and performance optimization
Desire candidate
- Candidate should have valid PF.
Regards,
NAM Info






