Full Stack Data Engineer

Ford Motor Company • Dearborn, MI

13h • $115,000 - $192,900 • 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're seeking a highly skilled and experienced Full Stack Data Engineer to play a pivotal role in the development and maintenance of our Enterprise Data Platform. In this role, you'll be responsible for designing, building, and optimizing scalable data pipelines within our Google Cloud Platform (GCP) environment. You'll work with GCP Native technologies like BigQuery, Dataflow, and Pub/Sub, ensuring data governance, security, and optimal performance. This is a fantastic opportunity to leverage your full-stack expertise, collaborate with talented teams, and establish best practices for data engineering at Ford.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, Information Systems, Data Analytics, or a related field (or equivalent combination of education and experience).
• 5-7 years of experience in Data Engineering or Software Engineering, with at least 2 years of hands-on experience building and deploying cloud-based data platforms (GCP preferred).
• Strong proficiency in SQL, Java, and Python, with practical experience in designing and deploying cloud-based data pipelines using GCP services like BigQuery, Dataflow, and DataProc.
• Solid understanding of Service-Oriented Architecture (SOA) and microservices, and their application within a cloud data platform.
• Experience with relational databases (e.g., PostgreSQL, MySQL), NoSQL databases, and columnar databases (e.g., BigQuery).
• Knowledge of data governance frameworks, data encryption, and data masking techniques in cloud environments.
• Familiarity with CI/CD pipelines, Infrastructure as Code (IaC) tools like Terraform and Tekton, and other automation frameworks.
• Excellent analytical and problem-solving skills, with the ability to troubleshoot complex data platform and microservices issues.
• Experience in monitoring and optimizing cost and compute resources for processes in GCP technologies (e.g., BigQuery, Dataflow, Cloud Run, DataProc).
• A passion for data, innovation, and continuous learning.

Responsibilities

• Spearhead the design, development, and maintenance of scalable data ingestion and curation pipelines from diverse sources. Ensure data is standardized, high-quality, and optimized for analytical use. Leverage cutting-edge tools and technologies, including Python, SQL, and DBT/Dataform, to build robust and efficient data pipelines.
• Utilize your full-stack skills to contribute to seamless end-to-end development, ensuring smooth and reliable data flow from source to insight.
• Leverage your deep expertise in GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Functions, etc.) to build and manage data platforms that not only meet but exceed business needs and expectations.
• Implement and manage robust data governance policies, access controls, and security best practices, fully utilizing GCP's native security features to protect sensitive data.
• Employ Astronomer and Terraform for efficient data workflow management and cloud infrastructure provisioning, championing best practices in Infrastructure as Code (IaC).
• Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions, ensuring optimal resource utilization and cost-effectiveness.
• Collaborate effectively with data architects, application architects, service owners, and cross-functional teams to define and promote best practices, design patterns, and frameworks for cloud data engineering.
• Proactively automate data platform processes to enhance reliability, improve data quality, minimize manual intervention, and drive operational efficiency.
• Clearly and transparently communicate complex technical decisions to both technical and non-technical stakeholders, fostering understanding and alignment.
• Stay ahead of the curve by continuously learning about industry trends and emerging technologies, proactively identifying opportunities to improve our data platform and enhance our capabilities.
• Translate complex business requirements into optimized data asset designs and efficient code, ensuring that our data solutions directly contribute to business goals.
• Develop comprehensive documentation for data engineering processes, promoting knowledge sharing, facilitating collaboration, and ensuring long-term system maintainability.

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: Mid Level