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Neimisha Konda
Senior Data Engineer specializing in Palantir Foundry and Snowflake for regulated industries
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Data engineer focused on high-volume transaction pipelines (2M+ per day) using Snowflake/Snowpipe, Spark/PySpark, Kafka, and Airflow, with a strong emphasis on schema/data-quality enforcement and reliability improvements. Also built a greenfield compliance-focused RAG solution, using CloudWatch monitoring and adding ingestion validation to prevent malformed OCR documents from degrading search quality.
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Key Strengths
- Owned end-to-end data pipeline processing 2M+ transactions/day
- Implemented schema checks and data quality rules in Spark/Snowflake to reduce downstream issues
- Built Python/PySpark transformations into clean Snowflake models for business consumption
- Improved ingestion reliability and reduced reconciliation issues via orchestration (Airflow) and validation
- Enabled self-serve access for fraud/compliance teams through Palantir Foundry governed datasets
- Delivered a greenfield RAG solution with CI/CD + CloudWatch monitoring; improved search quality by validating malformed OCR inputs
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