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Data Engineer- Full Stack

Job in Columbia, Lexington County, South Carolina, 29228, USA
Listing for: Ford Motor Company
Full Time position
Listed on 2026-02-18
Job specializations:
  • IT/Tech
    Data Engineer, Data Science Manager, Data Warehousing
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Location: Columbia

As a Senior Data Engineer, you will architect and scale end-to-end data pipelines on GCP, transforming complex telemetry and enterprise data into high-quality, analytics‑ready assets using Medallion architectures. You will lead the implementation of robust CI/CD workflows, rigorous data governance, and security controls while mentoring junior talent and driving engineering best practices. By collaborating with cross‑functional stakeholders and optimizing cloud performance, you will ensure the data platform remains secure, cost‑effective, and highly available to power critical business insights.

  • Operational Excellence: Using Terraform, Git, and Airflow to ensure reproducible, secure, and cost‑optimized cloud infrastructure.
  • Governance & Quality: Prioritizing data lineage, PII protection, and observability to maintain high trust in data assets.
  • Collaboration: Acting as a bridge between technical teams (Data Science, Security) and business stakeholders to deliver self‑service analytics.
  • Mentorship: Elevating the team through code reviews and documentation standards.
  • Technical Leadership: Designing end-to-end ETL/ELT pipelines and migrating assets to centralized platforms like Big Query.
Key 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., Big Query) 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 (Big Query, Dataflow, Dataproc, GCS).
  • Participate in on‑call rotations and incident response to maintain high availability of data services.
You’ll have…
  • Master’s Degree in Computer Science
  • 7 years of experience in data engineering, data platforms, or a similar role.
  • 4 years of hands‑on experience with Google Cloud Platform (Big Query, Cloud Storage, Dataflow, Dataproc; Schedule Query or equivalent scheduling/orchestration) or AWS.
  • 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.
Even better, you may have…
  • 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).

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!

Benefits
  • Immediate medical, dental,…
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