Data Engineer

Mission: Execute massive-scale asset rationalization, pipeline migrations, and programmatic metadata implementations using enterprise query, visualization, and telemetry tools. Core Responsibilities: • Asset Rationalization: Execute the migration, consolidation, or retirement of hundreds of legacy enterprise dashboards (Tableau, PowerBI) and data pipelines based on strict usage telemetry. • Programmatic Definitions: Write code that pushes metric definitions, dimensions, and owner mapping programmatically into central semantic catalogs via APIs. • Data Health Enforcement: Monitor real-time observability dashboards and resolve automated escalations regarding pipeline freshness lags or volume drops within strict SLAs. Requirements Tech Stack & Depth: • Core: Hive, Advanced SQL, Python for data manipulation, Airflow (or similar orchestration), Tableau / Enterprise Visualization tools. • Depth: Hands-on querying of massive distributed datasets (Hive/Presto/Trino) and telemetry logging. Must know how to trace complex data lineage manually through code. Good to Have / Bonus Tech Stack: • Experience with Databricks workflows and PySpark optimization. • Integrating automated testing in dbt. • Utilizing AI coding assistants for rapid SQL script generation and optimization.