Senior Director, Central Data Engineering at Ford Global Career Site

Dearborn, Michigan, United States -

Full Time

Start Date

Immediate

Expiry Date

03 Mar, 26

Salary

0.0

Posted On

03 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Architecture, Software Engineering, Google Cloud Platform, ETL, ELT, AI, Machine Learning, Data Governance, Data Quality, Data Security, SQL, Python, Java, Scala, Data Mesh

Industry

Motor Vehicle Manufacturing

Description

Serve as a primary strategic thought leader for the Data Platforms and Engineering organization, helping to shape the organizational strategy for how data is engineered, consumed, and leveraged across Ford. Advocate for the data strategy and navigate the complexities of implementation as it interfaces with diverse business units (e.g., Finance, Industrial Systems, Marketing) and other technical organizations. Articulate a clear vision and roadmap for Central Data Engineering that unifies our enterprise data strategy with broader business objectives. Champion the concept of "data as a product" at an enterprise scale, ensuring data assets are discoverable, addressable, trustworthy, and securely accessible to internal consumers. AI Readiness & Data Product Enablement: Drive the large Central Data Engineering organization to fundamentally improve Ford's AI data readiness. Collaborate closely with AI/ML teams, data scientists, and business leaders to understand critical AI requirements and ensure our data models are optimized to accelerate AI adoption and unlock enterprise value. Oversee the creation of well-modeled, high-quality data products that serve as the foundation for advanced analytics and generative AI applications. Lead the development of libraries and tools that enable standard patterns (e.g., bespoke libraries, common user-defined functions) to be used across all Data Engineering teams organization-wide. Attract, retain, develop, and promote top-tier technical talent, building a world-class engineering organization known for its expertise and innovation. Lead, mentor, and inspire Directors and Managers of data engineering, fostering a culture of technical excellence, and continuous improvement. Manage resource allocation and capacity planning for the Central Data Engineering team, balancing the delivery of broad/common datasets with ad-hoc enterprise requests. Technical Excellence & Standards: Hold the organization to the highest technical standards for code quality, operational stability, architecture, design, and execution. Enforce best practices across the Software Development Life Cycle (SDLC), ensuring sound architecture, rigorous testing, CI/CD implementation, and documentation standards. Lead the design and optimization of scalable, high-performance data pipelines (ETL/ELT) on Google Cloud Platform (GCP), utilizing services such as BigQuery, Cloud Storage, Dataflow, Dataproc, and Composer. Lead our Data Architecture organization to ensure the implementation of robust data models and with Privacy/Compliance teams to ensure all data practices meet stringent industry and regulatory requirements. Bachelor's degree in Computer Science, Engineering, or a related quantitative field (or equivalent combination of relevant education and experience). 12+ years of progressive experience in data engineering, data architecture, or software engineering. 5+ years of experience in a senior leadership capacity (Director level or above), managing large, layered technical teams and overseeing data-focused strategy. Deep expertise in Google Cloud Platform (GCP) data services (e.g., BigQuery, Dataflow, Cloud Storage, Dataproc, Pub/Sub, Composer) or equivalent hyperscaler technologies. Proven track record of designing and building scalable ETL/ELT pipelines and data warehousing solutions in a complex enterprise environment. Strong understanding of AI/ML concepts and experience engineering data specifically to support AI efforts. Demonstrated experience with data governance, data quality, and data security best practices. Proficiency in SQL and at least one major programming language (Python, Java, or Scala). Exceptional communication skills, with the ability to translate complex technical concepts into clear strategic vision for non-technical executive stakeholders. Master's degree in Computer Science, Engineering, or related field. Practical experience implementing Data Mesh principles or similar decentralized data architectures at scale. Experience with modern data stack tools and visualization platforms (e.g., Tableau, Power BI, Looker). 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 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. For more information on salary and benefits, click here: https://go.ford/LL4Benefits Visa sponsorship is not available for this position. Verification of employment eligibility will be required at the time of hire.

Responsibilities

Serve as a strategic thought leader for the Data Platforms and Engineering organization, shaping the organizational strategy for data engineering and consumption across Ford. Champion the concept of 'data as a product' and drive improvements in AI data readiness while overseeing the creation of high-quality data products.