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Saiprasad Barkam
Mid-level Data Engineer specializing in cloud ETL and streaming data pipelines
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About
Data engineer in healthcare/clinical data platforms (HarmonCare) who built and operated an end-to-end lakehouse pipeline ingesting HL7/FHIR at ~2–3M records/day on AWS (Glue/Lambda/S3/Spark) and serving trusted datasets in Snowflake. Implemented strong validation/reconciliation gates and a data quality framework that reduced discrepancies ~40%, plus CI/CD (GitHub Actions/Terraform) and monitoring (Airflow/CloudWatch).
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Key Strengths
- Owned end-to-end healthcare data pipeline ingesting HL7/FHIR at ~2–3M records/day
- Implemented data quality gates (schema/null/business rules) before promoting to final Snowflake tables
- Reduced data discrepancies by ~40% via data quality framework
- Designed resilient ingestion with retries (exponential backoff) and checkpointing to avoid duplication
- Built lakehouse-style transformations (bronze/silver/gold) using PySpark and dbt
- Set up CI/CD and infrastructure automation with GitHub Actions and Terraform plus CloudWatch monitoring/alerting
- Delivered internal REST APIs over curated Snowflake data with caching, query optimization, and versioned endpoints
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