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Enterprise Data Platform
Technology & Tools: Python, Java, SQL, PySpark, Apache Spark, Spark SQL, AWS, Amazon S3,
AWS Glue, PostgreSQL, Snowflake, BI, Terraform, ETL, ELT, Data Lake, Data Warehouse, Data
Lakehouse
Role: Data Engineer
• Designed scalable end-to-end ETL/ELT pipelines and batch data processing workflows
using Python, PySpark, Spark SQL, AWS, and Snowflake.
• Defined ingestion, transformation, validation, data flow, and data modeling patterns
for an enterprise Data Lake, Data Warehouse, and Data Lakehouse platform.
• Reviewed Spark execution plans and optimized transformations, joins, aggregations,
partitioning, and processing performance for distributed workloads.
• Used Terraform for Infrastructure-as-Code and collaborated across engineering,
product, and business teams to deliver scalable data solutions.
• Wrote and optimized Advanced SQL queries and supported data quality, reliability,
consistency, metadata, and governance requirements.
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