Data Engineer - Digital Analytics and Experimentation

The Data Engineer – Digital Analytics & Experimentation at Ford Motor will design, build, validate, and scale data foundations that power trusted digital measurement, KPI reporting, experimentation, AI‑enabled analytics, and enterprise digital data products across the DAE portfolio. The role involves translating analytical and product requirements into resilient data pipelines, reusable data assets, automated validation frameworks, and well‑documented data models to support digital analytics, personalization, and AI‑driven insights.

• 5+ years of experience in data engineering, analytics engineering, or related technical data roles
• 3+ years of hands‑on SQL experience building, transforming, joining, validating, and optimizing large‑scale datasets
• Experience building and maintaining data pipelines, ETL/ELT workflows, APIs, orchestration jobs, or production analytics datasets in a cloud or enterprise data environment
• Proficiency with Python, PySpark, dbt, Airflow, Dataflow, or Dataform
• Experience with cloud data platforms such as Google Cloud Platform, BigQuery, Cloud Composer, Cloud Functions, Pub/Sub, Dataproc, Snowflake, or Databricks
• Ability to document data lineage, business logic, technical assumptions, validation rules, and data quality considerations for cross‑functional audiences
• Strong written and verbal communication skills