@sathvikareddygaddam
Senior Data Engineer at CVS Health who built an Azure Databricks lakehouse processing 50M+ healthcare records daily.
United StatesAt CVS Health, I architected an Azure Databricks and Snowflake lakehouse that processes 50M+ healthcare records daily. I built near-real-time ingestion that cut data latency from hours to under 15 minutes.
Previously, I engineered toll transaction pipelines at North Texas Tollway Authority and PySpark pipelines at Reliance Jio. I also built an AI Stock Sentiment Analyzer with FinBERT, Streamlit, and Plotly.
Work history, roles, and key accomplishments
CVS Health
Jan 2026 - Present (10 months)
Architected a Medallion lakehouse on Azure Databricks and Snowflake processing 50M+ records daily. Built CDC-based near-real-time ingestion, tuned Spark workloads, enforced HIPAA-compliant governance, and implemented CI/CD with Azure DevOps and Terraform.
CVS Health
Jan 2026 - Present (10 months)
Architected a Medallion lakehouse on Azure Databricks and Snowflake processing 50M+ records daily. Built CDC-based near-real-time ingestion, tuned Spark workloads, enforced HIPAA-compliant governance, and implemented CI/CD with Azure DevOps and Terraform.
North Texas Tollway Authority
Jan 2025 - Dec 2025 (11 months)
Engineered ETL/ELT pipelines on Azure Databricks and Data Factory processing 5M+ daily toll transactions. Streamed Azure Event Hub data with Spark Structured Streaming for real-time fraud detection and designed star-schema models to improve query performance.
North Texas Tollway Authority
Jan 2025 - Dec 2025 (11 months)
Engineered ETL/ELT pipelines on Azure Databricks and Data Factory processing 5M+ daily toll transactions. Streamed Azure Event Hub data with Spark Structured Streaming for real-time fraud detection and designed star-schema models to improve reporting performance.
Built batch and near-real-time ETL pipelines in PySpark on Hadoop/HDFS processing 10M+ daily events. Ingested real-time streams with Apache Kafka, optimized PySpark jobs, and implemented data quality validation with Airflow.
Built batch and near-real-time ETL pipelines in PySpark on Hadoop/HDFS processing 10M+ daily events. Ingested real-time streams with Apache Kafka, optimized PySpark jobs, and implemented data quality validation with Airflow.
Degrees, certifications, and relevant coursework
Master of Science, Information Technology
2024 -
Pursuing a Master of Science in Information Technology, relocating to the United States in December 2024 for graduate studies.
Master of Science, Information Technology
2024 -
Pursuing a Master of Science in Information Technology, with relocation to the United States in December 2024 to begin graduate studies.
Software and tools used professionally
Amazon Redshift
Snowflake
Apache Spark
AWS Glue
Apache Flink
Tableau
Amazon S3
Google Cloud Storage
SonarQube
GitHub Actions
PySpark
dbt
MySQL
PostgreSQL
Hadoop
Databricks
Terraform
Azure DevOps
Python
Scala
MLflow
Streamlit
Azure Monitor
Amazon Kinesis
AWS Lambda
Git
Amazon EMR
SQL
Delta Lake
Great Expectations
Unity Catalog
Power BI
Apache Kafka
AWS
Azure
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