Aravind Swamy

I’m a Data Engineer with 2 years of experience building end-to-end ETL/ELT pipelines and dimensional data models using PySpark, AWS, Azure, Snowflake, and dbt. I bring a strong analytics engineering foundation from an MS in Data Analytics Engineering and a Cloud Big Data Masters Certification.

In my Data Engineer Intern role at DeepThink Health, I architected daily ingestion pipelines from S3 to Snowflake for claims, eligibility, and clinical data, orchestrating COPY INTO commands with Airflow to achieve a 99% load success rate. I built dbt Cloud staging-to-gold models, implemented 30+ dbt tests, and added column-level masking and row-level security in Snowflake—reducing data quality incidents by 90% while maintaining HIPAA-compliant PHI protection.

I also strengthened end-to-end delivery by orchestrating transformation runs through dbt Cloud’s native job scheduler and ingestion through Airflow, maintaining 99% on-time delivery within agreed service windows. By integrating Snowflake with a patient care management UI and Power BI, I helped drive a 20% reduction in hospital readmission rates, and I built DAX/Power Query dashboards that reduced Snowflake compute costs by 30%.

Earlier at Cognizant Technology Solutions, I built Azure Data Factory pipelines to extract data from on-prem Oracle systems into ADLS Gen2 for a large cloud migration, and I developed PySpark notebooks in Databricks to cleanse and transform 20+ TB of raw data, cutting processing time by 60%. I delivered CI/CD practices with Azure DevOps across development/test/production and supported fact/dimension migrations into Azure Synapse with 99% data integrity, while Power BI reporting contributed to a 15% revenue increase from high-margin travel packages.