- Design, develop, and maintain scalable data pipelines using PySpark and Python.
- Build ETL/ELT frameworks for ingesting, transforming, and loading large datasets.
- Develop Spark jobs for data cleansing, transformation, aggregation, and validation.
- Optimize Spark applications for performance using partitioning, caching, broadcast joins, and tuning techniques.
- Work with structured and unstructured data from multiple sources.
- Implement batch and real-time data processing solutions.
- Develop and optimize SQL queries, stored procedures, and data models.
- Collaborate with business analysts, architects, and data scientists to deliver data solutions.
- Ensure data quality, governance, security, and compliance standards.
- Implement CI/CD and DevOps practices for data engineering workloads.
- Troubleshoot production issues and provide operational support.
📌 Walk-in || Pyspark Data engineer (Pune)
🏢 Tata Consultancy Services
📍 Pune
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