Data Engineer,DIgital Analytics and Experimentation
Ford Motor Company (company site, opens in a new tab)5+ yrsChennaiHybridDirect career pageEst. 18–30 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Design, build, and maintain scalable data pipelines and curated assets for digital analytics, KPI reporting, experimentation, and AI-enabled insights across Ford’s global digital ecosystem.
- Collaborate with analytics leads, product managers, and data platform teams to translate requirements into reusable data models, automated validation frameworks, and governed data products supporting Power BI and advanced analytics.
- Implement automated data quality checks, monitoring, and validation to ensure trusted digital measurement, while applying modern engineering and AI tools for efficient analytics delivery.
Minimum Requirements
- Bachelor’s degree in Computer Science, Data Engineering, Data Science, Information Systems, Engineering, Statistics, Mathematics, or related field or equivalent experience.
- 5+ years of experience in data engineering, analytics engineering, or related technical data roles.
- 3+ years of hands-on SQL experience building and optimizing large-scale datasets plus experience with Python, PySpark, dbt, Airflow, Dataflow, Dataform, or similar data engineering tools.
- Experience supporting digital analytics, product analytics, customer analytics, experimentation, or self-service reporting use cases.
Ideal Candidate Profile
- Experienced in global, complex digital analytics environments combining clickstream, CRM, campaign, product, and transactional data.
- Proficient in designing governed, reusable data products and semantic models for enterprise BI tools like Power BI, with strong data lineage and documentation practices.
- Demonstrates practical fluency applying AI tools responsibly to automate data engineering tasks and accelerate modern analytics delivery with robust governance.