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Sri Vupp

@srivupp

Senior Data Engineer at Department of VA, building governed Databricks lakehouse platforms and optimizing Snowflake analytics workloads.

United States

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At Department of VA, I design lakehouse architecture and develop production data solutions with Databricks, Spark, and Delta Lake. I build pipelines that integrate databases, APIs, files, and cloud storage, with validation and recovery controls.

I also optimize Spark workloads and Snowflake queries, and develop governed analytics layers using Unity Catalog, dimensional models, and secure data access. My work includes CI/CD automation, observability, and production support.

Previously, at JPMC, I designed data pipelines and Airflow orchestration patterns for batch and streaming workloads. Earlier, I built cloud migration pipelines at DSV Logistics, including Python and PySpark workflows that moved 10TB+ of data to cloud warehouses.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Department of VA

Jun 2024 - Present (2 years 4 months)

Designed enterprise lakehouse architecture and developed scalable data solutions using Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, Unity Catalog, Python, and SQL for high-volume batch and distributed processing. Built production ETL/ELT pipelines with data contracts, CDC, automated validation, and monitoring.

Databricks Apache Spark PySpark Spark SQL Delta Lake Unity Catalog Python SQL Azure Data Factory ADLS Snowflake GitHub Actions Terraform CI CD Data Modeling ETL ELT Data Governance Observability

Senior AWS Data Engineer

JPMC

May 2022 - May 2024 (2 years)

Designed and developed enterprise data pipelines using Python, PySpark, Apache Spark, SQL, Databricks, Snowflake, AWS services, and Airflow for high-volume batch and analytical workloads. Led technical design reviews, reusable framework development, and production operations.

AWS Databricks Apache Spark PySpark Python SQL Snowflake Airflow Kafka S3 Glue EMR Redshift Git CI CD Data Engineering ETL ELT

Multicloud (AWS & GCP) Data Engineer

Best Buy

Jun 2021 - Apr 2022 (10 months)

Built cloud data pipelines using Python, PySpark, SQL, BigQuery, Cloud Storage, Cloud Composer/Airflow, Dataproc/Spark, Pub/Sub, and AWS services for scalable batch and streaming analytics workloads. Implemented data modeling, source-to-target mapping, and data-quality validation.

GCP BigQuery Cloud Storage Cloud Composer Airflow Dataproc Pub Sub Python PySpark SQL ETL ELT Git CI CD AWS

Python Developer | Data Engineer

Teledoc

Aug 2019 - May 2021 (1 year 9 months)

Developed Python-based ETL pipelines and AWS data solutions using Lambda, Glue, S3, Redshift, SQL, and PostgreSQL for high-volume healthcare data processing and analytics. Developed and maintained Informatica PowerCenter mappings and Oracle SQL/PL-SQL stored procedures.

Informatica PowerCenter Oracle SQL Pl SQL Python AWS Lambda AWS Glue S3 Redshift Control M Informatica PostgreSQL ETL Data Warehouse

Python Developer

DSV Logistics

Jan 2017 - Dec 2018 (1 year 11 months)

Built cloud migration pipelines with Python and PySpark replicating 10TB+ data from on-premise databases to cloud data warehouses (BigQuery, Snowflake) reducing infrastructure costs by 60%. Developed Python ETL workflows processing 500GB+ daily with data quality validation and automated monitoring.