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

• 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 Py. Spark optimization.
• Integrating automated testing in dbt.
• Utilizing AI coding assistants for rapid SQL script generation and optimization.