Build and maintain Snowflake data pipelines for Dealer 360 and Aftermarket workstreams.
Design and implement dealer and aftermarket feature stores (Layer 1–2).
Build ingestion pipelines for external data sources (JD Power, PIN, S&P, Vehicle Registration, competitive scraping + 2 TBC).
Write and maintain dbt models for data transformation, cleaning, and normalisation.
Enforce schema validation, data quality checks, and freshness SLAs across all feeds.
Collaborate with the Data Architect to implement the unified data model.

🎯 Requirements

8+ years in data engineering on cloud platforms.
Snowflake — data modelling, query optimisation, staging environments.
Python — pandas, PySpark, data pipeline scripting.
Experience building feature stores for ML consumption.
Strong understanding of schema design and dimensional modelling.
Nice to have: Azure — Data Factory, Blob Storage, or Synapse.

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