Key Responsibilities

- Design, develop, and maintain scalable data pipelines using Python and PySpark.

- Build and manage ETL/ELT workflows for processing structured and unstructured data.

- Develop and optimize Spark applications to handle large-scale datasets efficiently.

- Implement cloud-native data solutions using AWS services.

- Design and maintain Data Lakes on AWS.

- Perform data ingestion from multiple sources including APIs, databases, files, and streaming platforms.

- Monitor, troubleshoot, and optimize data workflows for performance and reliability.

- Ensure data quality, integrity, security, and governance standards are followed.

- Implement automation and orchestration of data workflows using scheduling tools.

- Collaborate with cross-functional teams for requirement gathering and solution design.

- Conduct code reviews, unit testing, and performance tuning.

- Prepare technical documentation and deployment procedures.

- Support production incidents and perform root cause analysis.

Mandatory Skills

- Robust expertise in Python

- Hands-on experience with PySpark

- Proficiency in SQL and query optimization

📌 AWS Data Engineer (Chennai)
🏢 Cognizant
📍 Chennai