F

Ford Motor Company

Builds vehicles for drivers and commercial fleets

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-time$115k - $192.9kRemote

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or an equivalent combination of relevant education and experience.
  • At least five years of experience in data engineering, software engineering, or a full-stack data role.
  • At least three years in roles demonstrating strong programming skills in Python, Kotlin, and Java.
  • At least three years of hands-on experience with Google BigQuery, including data modeling, query optimization, cost management, and scheduled queries.
  • At least three years of experience designing and building APIs using REST and/or GraphQL with frameworks such as FastAPI, Flask, Node.js/Express, or similar.
  • Three years of practical experience building and maintaining a semantic layer to standardize business metrics.
  • At least two years of experience in roles requiring a strong understanding of testing, monitoring, reliability, and maintainable software design.
  • At least two years of experience with SQL and structured data.
  • Legally authorized to work in the United States.

Responsibilities

  • 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, such as LookML, dbt semantic models, or Cube.js, that translates raw data into consistent, business-friendly metrics and definitions.
  • Implement and maintain a data catalog or knowledge catalog to improve data discoverability, lineage tracking, and metadata management.
  • Optimize BigQuery performance through partitioning, clustering, query tuning, and cost-management practices.
  • Build data quality checks, monitoring, and alerting to ensure pipeline reliability and data trustworthiness.
  • Collaborate with analytics, product, and engineering teams to gather requirements and translate them into scalable data models and API contracts.
  • Enforce data governance, security, and access-control standards, including personally identifiable information handling, role-based access, and encryption.
  • Write clean, well-tested, and maintainable code using Python, SQL, and backend frameworks for APIs.
  • Participate in code reviews, architecture discussions, and CI/CD pipeline development for data and application deployments.

Desired Qualifications

  • A master's degree in Computer Science, Engineering, Information Systems, or a related field.
  • Experience with data catalog or metadata management tools such as Google Data Catalog, Collibra, Alation, Atlan, or 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, including Cloud Storage, Cloud Functions, Dataflow, Pub/Sub, and Composer/Airflow.
  • A solid understanding of data modeling concepts, including dimensional modeling, star/snowflake schemas, and normalization.
  • Familiarity with version control using Git and CI/CD practices for data and application deployments.
  • A strong understanding of data governance, security, and privacy best practices.
  • Experience with orchestration tools such as Apache Airflow or Cloud Composer.
  • Familiarity with dbt for data transformation and testing.
  • Experience with containerization using Docker or Kubernetes and infrastructure-as-code using Terraform.
  • Exposure to streaming data platforms such as Kafka, Pub/Sub, or Dataflow.
  • Experience in the automotive, manufacturing, or connected vehicle data domain.
  • Knowledge of business intelligence and visualization tools such as Looker, Tableau, or Power BI.
  • Understanding of data mesh or domain-driven data architecture principles.

About the Company

Ford Motor Company

Builds vehicles for drivers and commercial fleets

Ford Motor Company designs and builds vehicles for individual drivers and commercial fleets worldwide, spanning Ford trucks and SUVs and Lincoln luxury models. Its Mustang sports car and Bronco off-road vehicles sit alongside gasoline, hybrid and electric products. The company sells vehicles, parts and accessories through dealers, while Ford Pro combines commercial vehicles with fleet software, charging and maintenance services; Ford Credit earns money from customer and dealer financing and leases. Connected services add subscriptions for vehicle features and business operations. Founded by Henry Ford in 1903, the company is headquartered in Dearborn, Michigan.

Company size
10,001+
Company stage
IPO
Headquarters
Dearborn, MI
Founded
1903

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