Top Data Engineer Jobs in Pune

Administer and optimize Cloudera CDP/CDH platforms (HDFS, Hive, Spark, YARN, Hue, CDE). Develop and deploy PySpark/Python data processing, build CI/CD pipelines with Jenkins and GitHub/Bitbucket, integrate SAST (Checkmarx), tune SQL/Impala performance, monitor platform health, perform upgrades, troubleshoot, and implement security, access management, and governance.

The Senior Software Engineer - Data Engineer will lead project phases, design technical solutions, manage team efforts, and collaborate globally while driving innovative data solutions.

The Data Engineer will design, develop, and maintain ETL/ELT data pipelines, leveraging PySpark and Databricks to process large datasets, ensuring data quality, reliability, and performance optimization.

Build, test, and maintain GCP-based data pipelines and ETL/ELT processes using Python and SQL. Optimize BigQuery queries, design data models, ensure data quality, troubleshoot pipeline issues, document solutions, and collaborate with analysts and engineers to deliver scalable data warehouse solutions.

Build and maintain cloud-based data products using Snowflake and big-data tools. Implement, test, and deploy data workflows with CI/CD, support production incidents and client onboarding, and collaborate in Agile teams while documenting solutions.

Design, build, and maintain data pipelines, data warehouses and data lakes to ensure accurate, accessible, and secure data. Develop processing and analysis algorithms and collaborate with data scientists to deploy ML models. Lead or advise teams, partner with stakeholders, manage risk and controls, and drive continuous improvement across data operations.

Designs, builds and maintains data pipelines, data warehouses and data lakes; implements processing and analysis algorithms; ensures data accuracy, security and accessibility; collaborates with data scientists to deploy ML models; may lead and supervise a team and enforce risk, controls and governance.

Design, build, and maintain scalable data pipelines, warehouses, and lakes. Implement processing and analysis algorithms, ensure data privacy and compliance, optimize performance, and collaborate with data scientists to deploy ML models. Lead or mentor teams, partner with stakeholders, and drive continuous improvement and risk controls.

Build and maintain data pipelines, warehouses and lakes; design architectures for secure, scalable data processing; develop processing algorithms; collaborate with data scientists to deploy ML models; lead or support team members and embed risk, controls and governance.

Design, build, and maintain cloud data pipelines, data warehouses and data lakes. Develop processing and analysis algorithms, ensure data quality, security and accessibility. Collaborate with data scientists to deploy ML models. Provide leadership or senior individual-contributor guidance, influence stakeholders, manage risk and strengthen governance.

The Data Engineer will support data governance practices by onboarding datasets, maintaining metadata, monitoring data quality, and assisting in engineering tasks like writing SQL queries and using data tools.

The Senior Azure Data Engineer will design, develop, and maintain data infrastructure and pipelines, ensuring data quality, integrity, and alignment with business objectives. Responsibilities include collaborating with teams and establishing best practices for data engineering.

Build and maintain scalable Azure and Databricks ETL/ELT pipelines using SQL and Python/PySpark. Design cloud-native data lakes, ingest/process data with ADF/ADLS, optimize data models, monitor pipeline health, troubleshoot failures, and collaborate with architects, QA, DevOps, and business teams.

Design, develop and deploy data engineering solutions and components (Java/Scala, Spark/Beam) on cloud/on-prem. Build and maintain data workflows, infrastructure-as-code, CI/CD, unit and integration tests, troubleshoot L3 issues, support releases, and produce product documentation and training materials. Collaborate across the SDLC and contribute to architecture, QA and continuous improvement.

Design, develop, test and deploy data engineering components and workflows (on‑prem/cloud). Implement pipelines using Java/Scala, Spark/Beam, GCP, Airflow; support L3 debugging, CI/CD, infrastructure as code, release deployments, documentation, and code reviews.

Lead design, build and maintenance of data pipelines, warehouses and lakes; develop processing/analysis algorithms; collaborate with data scientists to deploy ML; set strategy, manage resources, enforce controls, and engage stakeholders to deliver scalable, secure data solutions.

Design, build, and maintain Azure-based data infrastructure and pipelines. Implement data models and schemas, ensure data quality, optimize distributed storage and processing (Databricks/PySpark), and establish engineering best practices while partnering with cross-functional teams.

Design, build, and deploy production-grade AWS data services and ETL pipelines using PySpark and AWS Glue. Perform data modeling, data warehousing, and advanced SQL development; automate CI/CD and Lambda workflows; work with Redshift/RDS and large datasets to extract and transform data for analytics.

As a Data Engineer, you will develop and maintain data systems, build pipelines, design data architectures, and collaborate with data scientists to implement machine learning models.

Build, maintain and secure data pipelines, warehouses and lakes; design processing algorithms; collaborate with data scientists to deploy ML models; lead teams, manage risk and embed controls; partner with stakeholders to ensure accurate, accessible data.

Design, build, and maintain scalable data pipelines, warehouses, and lakes on cloud platforms. Implement real-time streaming (Kafka, Flink), parse payment message formats (ISO20022, SWIFT), transform data into AVRO schemas, integrate with IBM MQ/Kafka, collaborate with data scientists on ML model deployment, lead and coach teams, ensure security, testing, and operational controls.

As an Azure Data Engineer, you will innovate and maintain data engineering services for Fortune clients, develop software for large projects, and utilize Azure components for solutions.

Design, develop and deliver scalable AWS-based data solutions and ETL pipelines using Python/PySpark, Snowflake, and AWS analytics services. Collaborate across teams, implement secure coding and unit testing, optimise data ingestion and transformations, and support project delivery and stakeholder engagement.

The Data Engineer is responsible for building and maintaining data architectures, creating data pipelines, and developing algorithms for data processing and analysis. This role involves collaboration with data scientists and requires strong technical expertise, leadership skills, and a commitment to innovation and operational excellence.

Build and maintain scalable Azure cloud data platforms and ETL/ELT pipelines using Databricks, Synapse, ADF, ADLS. Develop SQL and Python/PySpark transformations, monitor pipeline health, troubleshoot failures, and collaborate with architects, QA, DevOps, and business stakeholders.