Senior Data Engineer, Integrated Services Data Warehouse (ISDW)

Ford Motor • Dearborn, MI

18h • Hybrid

About The Position

We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters. Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics and analytics, as well as insightful interpreters and analysts. That's where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making. We are seeking an exceptional, highly experienced Senior Data Engineer to join our team. In this role, you will design, build, and scale our next-generation big data infrastructure on Google Cloud Platform (GCP) and integrate state-of-the-art Agentic AI systems. You will play a pivotal role in enabling real-time data streaming, advanced analytics, and automated decision-making pipelines that directly influence our global subscription and integrated services products. If you are passionate about high-performance computing, distributed architectures, and building intelligent agents that operate on massive datasets, we want to hear from you.

Requirements

• Bachelor’s Degree in Computer Science, Information Technology, Software Engineering, or a closely related engineering field.
• 7+ years of hands-on experience in building, managing, and scaling enterprise-grade Big Data platforms and distributed data systems.
• 6+ years of strong, hands-on experience writing production-grade PySpark code, with deep knowledge of Spark optimization techniques, partition tuning, memory management, and debugging.
• 3+ years of experience architecting and implementing data solutions on GCP, with deep technical proficiency in: BigQuery: Advanced analytical SQL, partitioning, clustering, and performance optimization. Dataflow & DataProc: Managed Apache Beam pipelines and Spark/Hadoop clusters. Spanner: High-availability relational database workloads. Astronomer / Apache Airflow: Sophisticated DAG orchestration and workflow scheduling.
• Hands-on experience building and deploying Agentic AI solutions (e.g., autonomous AI agents, multi-agent orchestrations, tools integration with LLMs, prompt engineering frameworks, and cognitive search applications).
• Hands-on experience building, maintaining, and automating robust CI/CD pipelines (utilizing tools such as GitHub Actions, GitLab CI, Tekton, Jenkins, or equivalent) to deploy data models, code, and infrastructure.
• Practical familiarity with Integrated Services and Subscriptions platforms (such as subscription billing lifecycles, user entitlement systems, usage-based billing, and digital customer journeys).

Nice To Haves

• Master of Science (M.S.) in Computer Science, Data Engineering, or a highly quantitative field is a strong plus.
• GCP Professional Data Engineer Certification is a plus.
• GCP Professional Cloud Architect or equivalent Cloud Developer Certifications are a plus.
• Strong proficiency in modern programming languages (Python is required; Scala, Java, or Go is a plus).
• Experience with Infrastructure as Code (IaC) tools, particularly Terraform, for managing cloud infrastructure.
• Hands-on experience with containerization and orchestration platforms, including Docker and Kubernetes (GKE).
• Solid understanding of relational and NoSQL databases, data warehousing concepts, and data lakehouse architectures (e.g., Delta Lake, Iceberg).
• Excellent analytical, problem-solving, and debugging skills.
• Outstanding communication skills, with the ability to articulate complex technical architectures to both technical and non-technical stakeholders.

Responsibilities

• Architect, construct, and optimize highly scalable, reliable, and secure end-to-end data ingestion, processing, and distribution pipelines.
• Leverage PySpark and Google Cloud technologies to process terabyte-to-petabyte-scale datasets, ensuring optimal execution performance and cost-efficiency.
• Design, deploy, and maintain robust Agentic AI solutions (including LLM-based autonomous agents, retrieval-augmented generation (RAG) systems, vector database integrations, and automated tool-use pipelines) that run on top of enterprise data assets.
• Establish, maintain, and advocate for modern CI/CD practices across data engineering pipelines, ensuring automated testing, integration, and continuous deployment of data code and ML/AI models.
• Partner with product and platform teams to design data models supporting complex subscription metrics, recurring billing, customer entitlements, metered usage, and churn predictive analytics.
• Collaborate closely with Data Scientists, AI Researchers, Product Managers, and Software Engineers to align data architectures with strategic business objectives.
• Mentoring and guiding junior engineers in technical best practices.
• Champion enterprise-grade data security, regulatory compliance (e.g., GDPR, CCPA), and data quality monitoring across all platform components.

Benefits

• Immediate medical, dental, vision and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up childcare 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior