Strong hands‑on experience with AWS data services - S3, Glue (Jobs, Crawlers, Data Catalog), RDS, Redshift, Lambda, S3
2. Strong experience writing AWS Glue ETL jobs using PySpark - Glue DynamicFrames Spark DataFrame conversions ; Custom transformations, schema evolution, and job parameterization
3. Experience developing AWS Lambda functions using Python - Event‑driven processing (S3, Glue, Step Functions triggers)
4. Hands on PySpark experience for large scale data processing - DataFrame APIs, Spark SQL, joins, aggregations, window functions, Performance tuning (partitioning, caching, broadcast joins)
5. Proficiency in SQL (advanced queries & tuning) alongside Python/PySpark pipelines
