● Bachelor degree in Computer Science, IT, Engineering, Mathematics, Statistics, Data Science, or related — this is a Yes/No knockout, verify it, no equivalency assumptions.
● 5+ years as a Data Engineer and/or Data Analyst.
● 5+ years Python (incl. PySpark) + SQL for enterprise-grade ETL/ELT in large-scale cloud environments — the tallest technical bar.
● 4+ years each: BI/executive reporting (dashboards, KPI, self-service BI); cloud or hybrid data platforms; data warehouse/lakehouse design (star/snowflake, fact/dimension); ETL processes and tools.
● 2+ years data migration and modernization (on-prem, cloud, cross-database).
Note the shape of this role: it's a hybrid engineer + analyst. Power BI/DAX and executive reporting depth is a MUST-HAVE (4 yrs), not a nice-to-have — pure pipeline engineers without BI delivery will fail that row. Differentiators: public-sector enterprise apps (2 yrs), Fabric/Databricks/Spark/Delta Lake, AI-assisted development (Copilot etc.), DevOps/CI-CD/IaC.

Senior Data Engineer

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