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Naga Yanala
Mid-level Data Engineer specializing in cloud data pipelines and analytics platforms
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Data engineer with healthcare and enterprise experience (Molina Healthcare, Dell Technologies) building and operating high-volume batch + streaming pipelines across AWS and Azure. Strong focus on data quality (schema validation, fail-fast checks), reliability (monitoring/alerts, retries), and performance tuning (Spark/partitioning), with measurable runtime reduction and improved downstream trust.
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Key Strengths
- Owned end-to-end claims/eligibility data pipeline on AWS (S3/Glue/Airflow) processing ~400K+ records/day
- Improved pipeline performance by cutting runtime from ~2 hours to ~1 hour via validation and transformation optimizations
- Implemented strict schema validation to fail fast and prevent bad downstream data; increased analyst trust in outputs
- Built resilient external API ingestion on Azure (ADF/Databricks) with retries, monitoring/alerts, and rate-limit handling (~300K+ records/day)
- Debugged post-launch data correctness issues using logs and row-count comparisons; added additional validation to prevent recurrence
- Experience tuning Spark streaming jobs (partitioning, memory/parallelism) to reduce lag under higher volumes
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