Open to opportunities

Satarupa Mukherjee

@satarupamukherjee

Data Engineer building scalable AWS ETL/ELT pipelines with PySpark, Airflow, and Snowflake—focused on quality, performance, and BI-ready data.

India

Message

What I'm looking for

I’m looking for a Data Engineer role where I can own end-to-end ETL/ELT pipelines in AWS/Snowflake, strengthen data quality and testing, and optimize performance—while partnering with stakeholders to deliver BI-ready datasets. Open to relocate (Immediate).

I’m a Data Engineer at EXL Services, where I build and maintain scalable ETL/ELT pipelines on AWS to produce analytics-ready datasets in Amazon Redshift. I design modular PySpark and Spark SQL pipelines with incremental loading, and I manage Apache Airflow DAGs to ensure reliable execution with SLA monitoring.

I focus heavily on data quality—implementing null/duplicate validation, schema consistency checks, and data reconciliation—while optimizing SQL and Spark jobs for performance (improving performance by ~25%). I’ve also built Snowflake ELT workflows with dbt, reducing manual effort by ~30%, and delivered BI-ready outputs for Power BI/Tableau/QuickSight, cutting reporting effort by ~40%. I’m energized by ownership across end-to-end pipeline architecture, from source-to-target mapping and documentation to testing and debugging.

Experience

Work history, roles, and key accomplishments

Data Engineer

EXL Services

Aug 2023 - Jan 2026 (2 years 5 months)

Built and maintained scalable AWS-based ETL/ELT pipelines with Glue, S3, Lambda, Athena, and Lake Formation to generate analytics-ready datasets in Amazon Redshift. Developed PySpark/Spark SQL incremental transformations and Airflow DAGs with SLA monitoring, implemented data quality checks, and improved performance by ~25%, reduced Snowflake dbt manual effort by ~30%, and cut reporting effort by ~

Pyspark Apache Airflow AWS Glue Amazon S3 Amazon Redshift Data Quality DBT Snowflake