Data Engineer

📋 Description Reproduce a descriptive statistics report end-to-end with traceability to raw sources. Profile and reconcile differing source schemas into a conformed model. Build dbt staging, intermediate, and mart models with tests. Write Great Expectations suites and wire into the pipeline to fail bad data. Implement entity/identity resolution across sources. Orchestrate pipelines with Airflow/Step Functions for repeatable runs. 🎯 Requirements Strong SQL and Python for large-scale data processing. AWS data stack: S3, Glue, Lake Formation, Athena/Redshift, Spark, Step Functions. Data modeling & semantic layer (dbt or equivalent); dimensional modeling. Entity resolution across heterogeneous sources. Data-quality & testing frameworks (Great Expectations, dbt tests) and data lineage. Big-data processing (Spark) with performance and cost optimization.