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Tanvi Dasaripally
Mid-level Cloud Data Engineer specializing in Azure/AWS pipelines and medallion architecture
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About
Data engineer focused on reliability and data quality, owning end-to-end pipelines processing ~100k–300k records/day. Implemented robust validation and monitoring that cut reporting issues by ~30%, and built stable external data collection with anti-bot measures, backfills, and schema-change detection while maintaining backward-compatible internal data services.
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Key Strengths
- Owned end-to-end data pipelines (ingestion to reporting/serving)
- Implemented data quality controls (duplicates/nulls/row-count mismatches)
- Reduced reporting issues by ~30% via improved data quality checks
- Built reliable external data collection with monitoring, retries, and schema-change safeguards
- Anti-bot and stability practices (rate limiting, delayed retries, header rotation, batch processing)
- Shipped internal data services with performance tuning (better queries, smaller payloads)
- Managed backward compatibility through additive changes and explicit versioning
- Pragmatic scoping in ambiguous early-stage projects (batch vs real-time tradeoff)
- Set up CI, logging, and monitoring to support deployment and incident response
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