Hybrid Data Engineer

at Ford Motor Company

• Job title: Data Engineer
• Job type: Full Time
• Experience level: Senior, Lead
• Salary: $83,280 - $139,680 per year
• Degree requirement: Postgraduate Degree
• Tech skills: Airflow, BigQuery, Cloud, ETL, Google Cloud Platform, Grafana, PySpark, Python, Splunk, SQL, Tableau, Terraform
• Location requirements: Hybrid, Dearborn, United States

About the role

• Senior Data Engineer designing and operating scalable data pipelines on Google Cloud Platform. Leading data governance and collaborating with cross-functional teams for optimized data solutions.

Responsibilities

• Design and implement end-to-end data pipelines (ETL/ELT) that ingest, process, and curate large-scale enterprise data, including telemetry/vehicle data and other structured/unstructured sources.
• Migrate and modernize data assets to a centralized data platform (e.g., BigQuery) using principled data lake/warehouse architectures (Bronze/Silver/Gold or Medallion architecture) to power analytics and reporting.
• Architect scalable data models and data warehouses, optimizing for query performance, maintainability, and cost efficiency.
• Develop and operate robust orchestration pipelines using Airflow/Astronomer or Schedule Query, with secure, reproducible CI/CD workflows (Terraform + Git).
• Build and maintain reliable data quality checks, lineage, and monitoring with observability tools (e.g., Splunk, Looker/Grafana/Tableau/Power BI dashboards) to rapidly detect and resolve data issues.
• Implement data governance, security, and compliance controls (data lineage, access controls, PII/PHI protection) in collaboration with security and privacy teams.
• Lead the design and delivery of analytics-ready data assets for cross-functional teams, including dashboards, alerts, and self-service analytics.
• Mentor and coach junior engineers, review code, and drive best practices in data engineering, testing, and documentation.
• Collaborate with data scientists, product managers, and business stakeholders to translate requirements into scalable data solutions and timely insights.
• Monitor cost and capacity planning for cloud resources; optimize storage and compute usage across GCP services (BigQuery, Dataflow, Dataproc, GCS).
• Participate in on-call rotations and incident response to maintain high availability of data services.

Requirements

• Bachelor's Degree and/or equivalent education and experience
• 7+ years of experience in data engineering, data platforms, or a similar role.
• 4+ years of hands-on experience with Google Cloud Platform (BigQuery, Cloud Storage, Dataflow, Dataproc; Schedule Query or equivalent scheduling/orchestration).
• 4+ years experience in Python and SQL; strong experience with PySpark is a plus.
• 4+ years experience with ETL/ELT design, data modeling, data warehousing, and data governance.
• Practical experience building and operating data pipelines with orchestration tools (Airflow/Astronomer; Schedule Query).
• Experience with infrastructure-as-code and CI/CD (Terraform, Git, and related tooling).
• Demonstrated ability to design and implement analytics-ready data assets and dashboards; familiarity with BI tools (Looker, Tableau, Power BI, Grafana) for monitoring and reporting.
• Strong communication skills and ability to work effectively with cross-functional teams (engineering, analytics, product, security).

Benefits

• Immediate medical, dental, vision and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
• Vehicle discount program for employees and family members and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
• Paid time off and the option to purchase additional vacation time.