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Albert Pimentel
Mid-level Data Engineer specializing in cloud data pipelines and enterprise data platforms
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About
Data engineer/backend engineer who owns large-scale, real-time event pipelines on AWS end-to-end, including a petabyte-scale CDC ingestion flow from multiple Postgres DBs into Redshift. Re-architected a legacy DynamoDB+S3 approach into a Delta Lake + DuckDB/PyArrow-compatible design, improving performance dramatically (e.g., ~600s to ~10s for 1k records) and increasing reliability at high file volumes.
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Key Strengths
- Owned end-to-end real-time event-based pipeline from ingestion through serving
- Designed and implemented Delta Lake-based redesign to replace inefficient DynamoDB+S3 querying approach
- Improved pipeline throughput from ~600s to ~10s for 1,000 records
- Scaled/architected for very large data volumes (petabytes; reliability issues previously at >50k records per file)
- Integrated legacy DuckDB SQL configs by translating via PyArrow to query Delta Lake directly
- Identified performance bottleneck in coupled validation and proposed decoupled architecture for event streamer API
- Delivered ambiguous early-stage file validation system (S3-triggered Lambda) with stakeholder-friendly outputs (Excel + email via SNS)
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