Data Engineer

This role sits at the intersection of data engineering, backend API development, and data governance, and is ideal for someone who enjoys owning a problem from database to endpoint to business-ready metric. You’ll work closely with data analysts, application developers, and business stakeholders to ensure data is accessible, reliable, well-documented, and easy to consume across the organization., We are looking for a Full Stack Data Engineer to design, build, and maintain end-to-end data solutions - from raw data ingestion and API development through to curated semantic layers that power analytics and business decision-making.

• Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver data from diverse sources into Google BigQuery and other cloud data platforms.
• Develop, document, and maintain RESTful/GraphQL APIs to expose data and services to internal applications, dashboards, and third-party consumers.
• Design and manage a semantic data layer (e.g., LookML, dbt semantic models, Cube.js, or similar) that translates raw data into consistent, business-friendly metrics and definitions.
• Implement and maintain a data catalog / knowledge catalog (e.g., Google Data Catalog, Collibra, Alation, Atlan) to improve data discoverability, lineage tracking, and metadata management.
• Optimize BigQuery performance through partitioning, clustering, query tuning, and cost-management best practices.

• Build data quality checks, monitoring, and alerting to ensure pipeline reliability and data trustworthiness. Collaborate with cross-functional teams (analytics, product, engineering) to gather requirements and translate them into scalable data models and API contracts.

• Enforce data governance, security, and access control standards (PII handling, role-based access, encryption).
• Write clean, well-tested, and maintainable code (Python/SQL, and backend frameworks for APIs).
• Participate in code reviews, architecture discussions, and CI/CD pipeline development for data and application deployments.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field or equivalent combination of relevant education and experience.
• 5+ years of experience in data engineering, software engineering, or a full-stack data role.
• 3+ years in roles demonstrating Strong programming skills in Python, Kotlin, and Java
• 3 years of Strong hands-on experience with Google BigQuery (data modeling, query optimization, cost management, scheduled queries).
• 3+ years of Proven experience designing and building APIs (REST and/or GraphQL) using frameworks such as FastAPI, Flask, Node.js/Express, or similar.
• 3 years of practical experience building and maintaining a semantic layer (e.g., dbt, LookML/Looker, Cube.js, AtScale) to standardize business metrics.
• 2+ years of experience in roles requiring a Strong understanding of testing, monitoring, reliability, and maintainable software design
• 2+ years comfortable working years of experience with SQL and structured data

Even better, you may have…

• Master’s degree in Computer Science, Engineering, Information Systems, or a related field
• Document data flows, API specifications, semantic definitions, and system architecture for internal and cross-team use.
• Experience working with a data catalog / metadata management tool (e.g., Google Data Catalog, Collibra, Alation, Atlan, Amundsen) including lineage, tagging, and governance workflows.
• Strong SQL skills and experience with Python for data pipeline development and automation.
• Experience with cloud platforms, preferably Google Cloud Platform (GCP) (Cloud Storage, Cloud Functions, Dataflow, Pub/Sub, Composer/Airflow).
• Solid understanding of data modeling concepts (dimensional modeling, star/snowflake schemas, normalization).
• Familiarity with version control (Git) and CI/CD practices for data and application deployments.
• Strong understanding of data governance, security, and privacy best practices.
• Experience with orchestration tools such as Apache Airflow / Cloud Composer.
• Familiarity with dbt (data build tool) for transformation and testing.
• Experience with containerization (Docker/Kubernetes) and infrastructure-as-code (Terraform).
• Exposure to streaming data platforms (Kafka, Pub/Sub, Dataflow).
• Experience in the automotive, manufacturing, or connected vehicle data domain (a plus, given Ford’s business context).
• Knowledge of BI/visualization tools (Looker, Tableau, Power BI).
• Understanding of data mesh or domain-driven data architecture principles.

You may not check every box, or your experience may look a little different from what we’ve outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:

• 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.

This position is a salary grade 8 and ranges from $115,000-$192,900. Final determination of salary grade will be based on candidate’s skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.

Designs and maintains end-to-end data solutions, including ETL/ELT pipelines, BigQuery platforms, APIs, semantic data layers, and data catalogs. Builds data quality monitoring, governance, security, and access controls while collaborating with analytics, product, engineering, and business teams. Requires strong Python, Kotlin, Java, SQL, API development, cloud data engineering, testing, and reliability experience. The summary above was generated by AI

Enterprise Technology plays a critical part in shaping the future of mobility. If you’re looking for the chance to leverage advanced technology to redefine the transportation landscape, enhance the customer experience and improve people’s lives, this is the opportunity for you. Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are., Ford Pro is a new global business within Ford committed to commercial customer productivity. Ford Pro delivers a work-ready suite of vehicles, accessories and services for virtually every vocation, backed by technology and engineered for uptime. A true one-stop shop, we offer a full portfolio of electrified and internal combustion vehicles designed to integrate seamlessly with the Ford Pro ecosystem, helping customers’ businesses thrive today and into the new era of electrification., Ford Pro Intelligence provides telematics and fleet management services to our commercial and fleet customers. Ford Pro products and services serve as a foundational building block to Ford’s continued leadership and innovation in fleet/commercial vehicle market segments. Fleets are our future, representing a significant portion of vehicle sales and continual expected growth.