Director, Data Engineering and Product Strategy at Ford Global Career Site

Dearborn, Michigan, United States -

Full Time

Start Date

Immediate

Expiry Date

12 Feb, 26

Salary

0.0

Posted On

14 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Architecture, Data Product Management, Leadership, Data Governance, Data Quality, AI/ML Concepts, Data Visualization, Agile Methodologies, Collaboration, Data Hub/Mesh Principles, Financial Data, Project Management, Innovation, Mentoring, Continuous Improvement

Industry

Motor Vehicle Manufacturing

Description

Articulate a clear vision and roadmap for Finance data products, unified with our enterprise data strategy and financial objectives. Champion the concept of "data as a product" within Finance, ensuring data assets are discoverable, addressable, trustworthy, and securely accessible to internal consumers, including AI/ML teams. Collaborate closely with Finance stakeholders, data scientists, and business leaders to understand critical data needs, define data product requirements, and establish clear SLAs. Bachelor's degree in Computer Science, Engineering, Finance, Economics, or a related quantitative field or equivalent combination of relevant education and experience. 8+ years of progressive experience in data engineering, data architecture, or data product management roles. 3+ years of experience in a leadership or management capacity, overseeing data-focused teams supporting finance Master's degree in Finance, Computer Science or related field Experience in automotive manufacturing supporting Finance. Practical experience implementing Data Hub/Mesh principles or similar decentralized data architectures. Familiarity with AI/ML concepts and their application in finance (e.g., forecasting, fraud detection, risk modeling). Experience with data visualization tools (e.g., Tableau, Power BI, Looker) Visa sponsorship is not available for this position. Verification of employment eligibility will be required at the time of hire. Ensure the reliability, efficiency, and cost-effectiveness of data solutions, leveraging GCP's managed services and best practices. Institute rigorous data governance frameworks for Finance data, data products, ensuring federated computational governance that adheres to enterprise standards, privacy regulations, and security protocols. Mandate and implement automated data quality checks, monitoring, and remediation processes to maintain the integrity and trustworthiness of all financial data products. Partner with legal and compliance teams to ensure all data practices meet stringent industry and regulatory requirements. Team Leadership & Development: Lead, mentor, and inspire a team of data engineers and data product owners, fostering a culture of technical excellence, continuous improvement, and innovation. Drive best practices in data engineering, data/ai/mlops readiness and agile methodologies within the team. Manage resource allocation, project timelines, and deliverables to ensure successful execution of data initiatives. Empower cross-functional collaboration between Finance, IT, AI/ML teams, and other business units to leverage integrated datasets for advanced analytics and AI applications. Actively explore and introduce innovative data technologies and methodologies, including synthetic data generation where appropriate, to solve complex financial challenges and accelerate AI adoption. Established and active employee resource groups

Responsibilities

Articulate a clear vision and roadmap for Finance data products, ensuring data assets are discoverable and trustworthy. Lead and mentor a team of data engineers and product owners, fostering a culture of technical excellence and innovation.