Data Engineer at SaaS Company strive to make selling fun with our SaaS incen · Bengaluru (Bangalore) · 4 - 8 years · ₹20L - ₹25L / yr · Posted 28 Jun 2022
PostgreSQL
Python
Amazon Web Services (AWS)What is the role?
You will be responsible for developing and designing front-end web architecture, ensuring the responsiveness of applications, and working alongside graphic designers for web design features, among other duties. You will be responsible for the functional/technical track of the project
Key Responsibilities
- Develop and automate large-scale, high-performance data processing systems (batch and/or streaming).
- Build high-quality software engineering practices towards building data infrastructure and pipelines at scale.
- Lead data engineering projects to ensure pipelines are reliable, efficient, testable, & maintainable
- Optimize performance to meet high throughput and scale
What are we looking for?
- 4+ years of relevant industry experience.
- Working with data at the terabyte scale.
- Experience designing, building and operating robust distributed systems.
- Experience designing and deploying high throughput and low latency systems with reliable monitoring and logging practices.
- Building and leading teams.
- Working knowledge of relational databases like Postgresql/MySQL.
- Experience with Python / Spark / Kafka / Celery
- Experience working with OLTP and OLAP systems
- Excellent communication skills, both written and verbal.
- Experience working in cloud e.g., AWS, Azure or GCP
Whom will you work with?
You will work with a top-notch tech team, working closely with the architect and engineering head.
What can you look for?
A wholesome opportunity in a fast-paced environment that will enable you to juggle between concepts, yet maintain the quality of content, interact and share your ideas and have loads of learning while at work. Work with a team of highly talented young professionals and enjoy the benefits of being at this company
We are
We strive to make selling fun with our SaaS incentive gamification product. Company is the #1 gamification software that automates and digitizes Sales Contests and Commission Programs. With game-like elements, rewards, recognitions, and complete access to relevant information, Company turbocharges an entire salesforce. Company also empowers Sales Managers with easy-to-publish game templates, leaderboards, and analytics to help accelerate performances and sustain growth.
We are a fun and high-energy team, with people from diverse backgrounds - united under the passion of getting things done. Rest assured that you shall get complete autonomy in your tasks and ample opportunities to develop your strengths.
Way forward
If you find this role exciting and want to join us in Bangalore, India, then apply by clicking below. Provide your details and upload your resume. All received resumes will be screened, shortlisted candidates will be requested to join for a discussion and on mutual alignment and agreement, we will proceed with hiring.
Shubham Vishwakarma
Full Stack Developer - Averlon
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Python
ScalaDescription
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.
PythonJob 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.
PythonAbout the Role
We are looking for a Senior Data Engineer with strong hands-on expertise in Databricks, Python, PySpark, and SQL to build scalable, high-performance data engineering solutions. You’ll architect and develop large scale, high-performance data pipelines capable of handling massive real-time and batch data volumes across multiple business systems. Databricks is the core enterprise data and processing platform for this role. You will also use Apache Airflow for workflow orchestration and dbt for ELT transformations, and will contribute to designing reliable, secure, and governed data platforms that enable analytics, reporting, and AI-driven use cases.
Key Responsibilities
- Design and implement large-scale data pipelines using Python/PySpark, Databricks, and Microsoft Fabric.
- Develop and optimize data processing workloads in Databricks using PySpark and Spark SQL, with a strong focus on scalability, reliability, performance, and maintainability.
- Develop and maintain dbt models including layered architecture, incremental models, snapshots, macros, testing, and documentation.
- Design, develop, and maintain Apache Airflow DAGs for orchestrating reliable, scalable, and observable data pipelines.
- Design and implement data quality, observability, and governance frameworks, including automated testing, monitoring, lineage, access control, and data privacy standards.
- Partner with analytics, product, and business stakeholders to turn requirements into trustworthy datasets, and raise the engineering bar through design discussions, code reviews, and mentoring junior engineers.
Required Skills
- Strong expertise in Python for developing scalable, modular, and production-ready data engineering applications.
- Strong expertise in PySpark, including DataFrame API, Spark SQL, Structured Streaming, partitioning strategies, joins, caching, handling data skew, and Spark performance optimization.
- Strong hands-on experience with Databricks for data ingestion, transformation, processing, and optimization, including Delta Lake, Unity Catalog, Databricks Workflows, notebooks, jobs, and Databricks-native data engineering capabilities.
- Strong experience in Databricks/Spark performance tuning, including query and job optimization, partitioning, file sizing, caching, join optimization, handling data skew, and efficient use of compute resources.
- Hands-on experience with Delta Lake, including transactional data processing, schema management, incremental data processing, and reliable batch and streaming data pipelines.
- Hands-on experience in developing dbt projects using layered architecture, incremental models, snapshots, macros/Jinja, testing, documentation, and deployment best practices.
- Expertise in advanced SQL and data modelling — dimensional modeling, slowly changing dimensions, schema evolution, and query optimization.
- Hands-on experience in developing and managing Apache Airflow DAGs, scheduling workflows, dependency management, retries, backfills, and operational monitoring.
- Hands-on experience with at least one major cloud platform (AWS, Azure or GCP).
- Strong problem-solving skills and the ability to work independently with business and analytics stakeholders.
Nice to Have
- Hands-on exposure to Microsoft Fabric for data integration and analytics.
- Experience using AI coding assistants (e.g. Claude Code, GitHub Copilot) as part of a development workflow.
- Familiarity with modern DevOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and containerization (Docker/Kubernetes).
- Domain expertise in financial services.
4 - 10 years of experience in designing and buildingarchitecting highly resilient data platforms
∙Strong knowledge of data engineering, architecture and data modeling
∙Experience in platforms like Databricks and Snowflake
∙Experience on building applications on cloud (AWS or Azure or Google Cloud)
∙Strong analytical and problem-solving skills
∙Prior experience in developing data or computation intensive (e.g. grid based) backend applications is an
advantage
∙OOP design skills with an understanding or at least personal interest towards the concepts of Functional
Programming
∙Willingness to understand and enhance other people’s code, being able to work in an environment where
developers will oversee and work on wider components also dealing with older “legacy” code
∙Strong programming skills (Java/ Scala / Python) skills with the willingness to pick up the other language if not
already mastered at a sufficient level is important
∙Spring knowledge is an advantage, but in general willingness to learn, work with and even enhance in-house
developed frameworks is a must
∙Prior experience in working with Git, Bitbucket, Jenkins, working with PR-s, using JIRA, following the Scrum Agile
methodology is an advantage
∙Prior knowledge of financial products is an advantage
∙Bachelors or Masters in any relevant field of IT/Engineering area is an advantage
PythonScalaJob Description:
Position: Lead / Senior Data Engineer
Location: Chennai
Shift: US Eastern Time ( 5:00 PM – 2:00 AM )
Experience : 8+ years
Notice Period: Immediate Joiner only
Roles and Responsibilities:
Role Overview
The Lead Data Engineer will be responsible for designing, developing, and delivering high-quality software and data solutions while leading a team of engineers. The role involves hands-on technical work, architectural decision-making, mentoring junior developers, and collaborating with cross-functional teams to ensure successful delivery of scalable data platforms and analytical solutions.
Key Responsibilities:
Lead the end-to-end design, development, and delivery of software systems, data pipelines, and components.
Define technical strategy, architecture, and best practices for development and data engineering.
Design and build optimized data pipelines using cutting-edge technologies in a cloud environment.
Construct infrastructure for efficient ETL processes from various sources and storage systems.
Architect, design, and maintain database pipeline architectures, ensuring readiness for AI/ML transformations.
Lead the implementation of algorithms and prototypes to transform raw data into useful information.
Review code for quality, scalability, and performance.
Collaborate with Product Managers, Business Managers, Designers, and QA teams to translate business requirements into technical solutions.
Develop analytical tools, programs, and reporting mechanisms.
Create data validation methods and data analysis tools.
Interpret data trends and patterns to establish operational alerts.
Conduct complex data analysis and present results effectively.
Prepare data for prescriptive and predictive modeling.
Ensure compliance with data governance and security policies.
Troubleshoot, debug, and resolve complex technical issues.
Drive continuous improvement in software and data development processes, tools, and methodologies.
Mentor and guide engineers through code reviews, technical discussions, and training.
Ensure timely delivery of projects while maintaining high engineering standards.
Continuously explore opportunities to enhance data quality and reliability.
Apply strong programming and problem-solving skills to develop scalable solutions.
Demonstrate passion for testing strategy, problem-solving, and continuous learning.
Willingness to acquire new skills and knowledge.
Possess a product/engineering mindset to drive impactful data solutions.
Experience working in distributed environments with global teams.
Stay current with emerging technologies and industry trends to propose innovative solutions.
Technical Skills and Experience Requirements
Minimum 8+ years of hands-on experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed data pipelines.
High proficiency in Python, Scala, and Spark for applied large-scale data processing.
Expertise with big data technologies, including Spark, Data Lake, Delta Lake, and Hive.
Solid understanding of batch and streaming data processing techniques.
Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion.
Expert-level ability to write complex, optimized SQL queries across extensive data volumes.
Experience with RDBMS and OLAP databases such as MySQL and Snowflake.
Familiarity with Agile methodologies.
Obsession for service observability, instrumentation, monitoring, and alerting.
Knowledge or experience in architectural best practices for building data lakes.
Qualifications - Bachelor’s degree in computer science, Engineering, Information Systems, or related field.
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
KubernetesScalaDescription
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.
PythonJob Summary
We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.
Technical Skills
- Strong hands-on experience in Python and PySpark development.
- Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
- Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
- Experience with Power BI Data Modeling and Semantic Layer development.
- Proficiency in DAX (Data Analysis Expressions).
- Experience designing and managing Semantic Models in Power BI.
- Strong SQL skills and experience working with large datasets.
- Knowledge of data warehousing concepts and best practices.
Preferred Skills
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Exposure to modern data platforms like Databricks.
- Understanding of data governance and data quality frameworks.
PythonSenior Data Engineer – PySpark & Oracle
Experience: 7+ Years
Location: Bangalore
Notice Period: Immediate to 10 Days
Key Skills:
- Strong expertise in Data Modeling, Data Design & Modernization
- Primary skills: PySpark, Oracle SQL/PLSQL
- Secondary skills: Python, ETL & Data Pipelines
- Experience with Kafka and Hadoop
- Exposure to AWS / Azure / GCP
- Good knowledge of Git and JIRA
Roles & Responsibilities:
- Design, develop, and modernize scalable data models and data architecture.
- Develop and optimize data processing solutions using PySpark and Oracle SQL/PLSQL.
- Build and maintain robust ETL workflows and data pipelines.
- Work with Kafka, Hadoop, and cloud platforms for data processing and integration.
- Perform data transformation, optimization, and performance tuning.
- Collaborate with technical teams on data design, development, testing, and deployment.
PythonJob 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
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon