This is a data engineering role focused on building and supporting end-to-end data pipelines—profiling source data, designing robust ETL/ELT, deduplicating and transforming datasets, and delivering analytics-ready outputs (often dimensional models). You’ll own testing (unit/functional/performance), tuning, and production support, while working closely with Product to refine requirements and with QA to resolve issues. Strong ownership and mentoring/onboarding are expected. Advanced SQL (CTEs, complex joins, window/analytic functions, performance tuning) Snowflake (warehouse development + ELT patterns) dbt (transformations, modeling, testing, documentation) Spark (large-scale transformations) Databricks (Spark-based pipelines and workflow orchestration) AWS (cloud data platform services for ingestion, storage, orchestration, and monitoring) Python (pipeline automation + data validation/testing)