Sr. Specialist, Yield Management - GTM Data Engineer

Sr. Specialist, Yield Management - GTM Data Engineer

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.

Our Marketing, Sales & Service organization advances the Ford reputation as a visionary vehicle and mobility services company and helps deliver a trusted customer experience. Use your marketing, sales and service expertise to turn data-driven insights into innovative solutions that enhance sales and customer loyalty. Join us and be the eyes, ears and voice of Ford.

In this position...

This role sits at the intersection of data engineering, business intelligence, data science, and data governance, and is ideal for someone who enjoys solving a business problem from raw datasets to endpoint to business-ready metric.

You'll work closely with data analysts, data scientists, and business stakeholders to ensure data and metrics are well-defined, accessible, reliable, well-documented, and easy to consume across the organization.

We are looking for a Data Engineer to design, build, and maintain end-to-end data solutions - from raw data ingestion through to curated metrics that power advanced analytics, business intelligence dashboards and business decision-making.

This role sits at the intersection of data engineering, business intelligence, data science, and data governance, and is ideal for someone who enjoys solving a business problem from raw datasets to endpoint to business-ready metric. You'll work closely with data analysts, data scientists, and business stakeholders to ensure data and metrics are well-defined, accessible, reliable, well-documented, and easy to consume across the organization.

What you'll do...

• Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver data from diverse sources into Google BigQuery and other cloud data platforms.
• Develop, document, and maintain curated business-ready metrics to expose data and metrics to internal advanced analytics AI/ML models, dashboards, and variety of consumers.
• Design and manage a curated data layer that translates raw data into consistent, business-friendly metrics and definitions.
• Design, build and manage business friendly dashboards that provide valuable business insights to the executive leadership

Implement and maintain a data catalog / knowledge catalog (e.g., Google Data

• Catalog) to improve data discoverability, lineage tracking, and metadata management.
• Optimize BigQuery performance through partitioning, clustering, query tuning, and cost-management best practices.
• Build data quality checks, monitoring, and alerting to ensure pipeline reliability and data trustworthiness.
• Collaborate with cross-functional teams (analytics, product, business) to gather requirements and translate them into scalable data models, metrics
• Enforce data governance, security, and access control standards (PII handling, role-based access, encryption).
• Write clean, well-tested, and maintainable code (Python/SQL, and backend frameworks for API based ingestion routines).
• Create and maintain CI/CD pipelines for seamless deployments and change reviews across the code base.
• Participate in code reviews, architecture discussions, and CI/CD pipeline development for data and application deployments.

What you'll do...

• Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver data from diverse sources into Google BigQuery and other cloud data platforms.
• Develop, document, and maintain curated business-ready metrics to expose data and metrics to internal advanced analytics AI/ML models, dashboards, and variety of consumers.
• Design and manage a curated data layer that translates raw data into consistent, business-friendly metrics and definitions.
• Design, build and manage business friendly dashboards that provide valuable business insights to the executive leadership

Implement and maintain a data catalog / knowledge catalog (e.g., Google Data

• Catalog) to improve data discoverability, lineage tracking, and metadata management.
• Optimize BigQuery performance through partitioning, clustering, query tuning, and cost-management best practices.
• Build data quality checks, monitoring, and alerting to ensure pipeline reliability and data trustworthiness.
• Collaborate with cross-functional teams (analytics, product, business) to gather requirements and translate them into scalable data models, metrics
• Enforce data governance, security, and access control standards (PII handling, role-based access, encryption).
• Write clean, well-tested, and maintainable code (Python/SQL, and backend frameworks for API based ingestion routines).
• Create and maintain CI/CD pipelines for seamless deployments and change reviews across the code base.
• Participate in code reviews, architecture discussions, and CI/CD pipeline development for data and application deployments.