Senior Data Engineer - AWS/Snowflake Pipeline Audit & Fix

We have an existing data pipeline (Python + AWS + Snowflake) that's underperforming, slow, unreliable, or not scaling well and needs a senior engineer to diagnose and fix it within 1-2 weeks. This is an audit + implementation engagement, not a build-from-scratch project. Scope of Work: - Review existing pipeline code (Python scripts, AWS setup, Snowflake schema/queries); access provided day 1. - Identify root cause(s): performance bottleneck, failure points, cost inefficiency, or data quality gap. - Implement fixes directly: query optimization, error handling, retry logic, warehouse sizing, or restructured dbt models. - Provide before/after benchmarks (run time, cost, or failure rate) - Short handoff doc: what was wrong, what was changed, follow-up recommendations Requirements: 1 - 5+ years of data engineering experience, production systems. 2 - Strong Python + AWS (S3, Lambda, IAM) hands-on experience. 3 - Snowflake performance tuning (query profiling, warehouse sizing, clustering); dbt experience a plus. 4 - Able to self-direct after a 30-min kickoff call. Deliverables: fixed/optimized pipeline, before/after metrics, handoff documentation Note: - Timeline: 1 - 2 weeks, starting within 2–3 days of hire. - Engagement Type: Hourly, possible follow-on work.