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Manasa Gunreddy
Senior Data Engineer specializing in cloud data platforms and real-time streaming
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About
Data engineer in healthcare (HCA) who owned end-to-end Azure-based pipelines at very large scale (50M+ daily claims/patient records). Strong focus on reliability: schema-drift fail-fast validation, quarantine layers, and Python/SQL data quality checks that reduced issues ~25%, plus performance tuning in Databricks/PySpark and versioned serving in Synapse for downstream consumers.
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Key Strengths
- Owned high-volume healthcare data pipelines processing 50M+ claims/patient records daily
- Reduced recurring data issues by ~25% via Python/SQL data quality checks and quarantine layer
- Handled schema drift with fail-fast schema validation and clear logging to prevent downstream breakages
- Improved Spark join performance using partitioning, shuffle reduction, and incremental processing
- Built curated data serving layer in Synapse with dataset versioning/backward compatibility
- Stood up MVP in ambiguous environment; aligned stakeholders on metrics and implemented CI/CD + observability
- Incident debugging across layers (schema change broke join causing reporting mismatches) and implemented preventative controls
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