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Varshitha K
Mid-level Data Engineer specializing in cloud data platforms and lakehouse architectures
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Data engineer in a banking context who has owned end-to-end Azure lakehouse pipelines ingesting financial/vendor data from APIs, Azure SQL, and flat files into Databricks/Delta (bronze-silver-gold). Emphasizes production reliability via schema-drift validation, data quality controls, monitoring/alerting, retries/checkpointing, and Spark/Delta performance tuning, with outputs served to BI/reporting teams (e.g., Tableau).
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Key Strengths
- Owned end-to-end Azure lakehouse pipelines (ingestion → validation → Databricks transforms → serving)
- Strong data quality engineering (schema drift handling, null/duplicate checks, count reconciliation, quarantine/failed-record handling)
- Performance and reliability optimization for Spark/Delta workloads (partitioning, Delta tuning)
- Operational rigor for external/vendor data ingestion (monitoring/alerting, retries, checkpointing)
- Delivered curated gold-layer datasets for analytics/reporting with stable, documented schemas
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