JOB DESCRIPTION

As the Supervisor, Data Platform for Supplier Collaboration, you will serve as the foundational leader responsible for the architecture, reliability, and scalability of the data ecosystem supporting Ford's global Supplier Collaboration modernization. While Data Engineering teams focus on building specific pipelines and models, your mission is to provide a world-class, cloud-native platform that enables seamless integration between internal systems - including MMP, CMMS, WIPS, WERS, GMM, and others - landing and transforming data to make it readily available to external interfaces such as E2Open, Resilinc, Circular, ISDP, and the GDIA Data Lake.

This platform is inherently operational and transactional in nature, driving real-time decision-making to proactively avoid and mitigate production disruptions that ultimately impact customer vehicle delivery and enterprise profitability. You will lead the Platform as a Product strategy to ensure the Supplier Collaboration Integrated Data Platform (IDP) is a high-performance, secure, and cost-efficient environment that drives transparency, resilience, and data-driven decision-making across Ford's global supplier network.

RESPONSIBILITIES

Operational Excellence & AI Readiness

Drive the platform organization to improve Ford's AI data readiness by providing the high-performance compute and storage infrastructure required for advanced analytics and Generative AI in the industrial space.
Establish a culture of Site Reliability Engineering (SRE) for the IDP, defining Service Level Objectives (SLOs) for platform uptime, data latency, and integration reliability.
Oversee the development of common infrastructure libraries and automation tools (e.g., Terraform modules, standard CI/CD patterns) to be leveraged by all engineering teams across the IDP platform.
Implement robust monitoring and observability frameworks to proactively identify and address bottlenecks in the global supplier collaboration data flow.

Technical Standards & Governance

Hold the organization to the highest technical standards for Infrastructure as Code (IaC), ensuring sound architecture, rigorous testing, and automated deployment via CI/CD pipelines.
Lead the design and optimization of the underlying infrastructure for scalable data services on GCP, including BigQuery, Dataflow, and Cloud Composer.
Partner with Cybersecurity and Privacy teams to enforce Security by Design, ensuring the platform meets stringent global regulatory requirements for industrial data.

Organizational Leadership & Talent Development

Attract, retain, and develop top-tier technical talent, building a world-class platform engineering organization specialized in cloud-native industrial systems.
Lead and mentor Tech Leads and Lead Engineers, fostering a culture of technical excellence, continuous improvement, and systems thinking.
Manage resource allocation and capacity planning, balancing the delivery of core platform features with the needs of the broader Supply Chain Collaboration strategic roadmap.
Organize and lead the team to drive repeatable and effective ETL/ELT of new data sources, with an emphasis on standardization and simplification.
Work closely with managers and stakeholders across the organization to understand data needs and priorities, and to develop and execute a data engineering roadmap that aligns with broader business objectives.

QUALIFICATIONS

Bachelor's degree in a technical or science-based discipline
3+ years of experience with SQL and Python
3+ years of experience with GCP cloud services strong candidates with 5+ years in a traditional data warehouse environment (ETL pipelines with Informatica) will be considered
3+ years of experience building data pipelines from scratch in a highly distributed and fault-tolerant manner
Proficiency with a broad array of relational and non-relational databases
Proven track record of building applications in a data-focused role, spanning both cloud and traditional data warehouse environments
Deep expertise in Google Cloud Platform (GCP) infrastructure and data services, including IAM, VPCs, BigQuery, Dataflow, Pub/Sub, and Cloud Storage
Proven track record of designing and building scalable, cloud-native platforms in a complex, global enterprise environment