Sr. Specialist, Yield Management - GTM Data Engineer

Lincoln Motor Company; Dearborn (MI); Hybrid; USD 115,000 - 193,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Parental leave and family care days

Tuition assistance

Vehicle discount program

Job summary

Ford Motor Company is seeking a Sr. Specialist focused on Yield Management GTM Data Engineering. You will design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver data for BigQuery and other cloud platforms, and develop business-ready metrics for analytics and dashboards.

The role covers data engineering, BI, data science, and governance, with emphasis on data quality, security, and cross-functional collaboration. Hybrid work in Dearborn, MI.

Qualifications

• Requires 5+ years in data engineering/software engineering/full-stack data roles.
• Proficient in Python and SQL with hands-on Google BigQuery/Dataflow experience.
• Experience building standardized data marts and BI dashboards.
• Strong understanding of data governance, security, and privacy practices.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines for data ingestion and delivery.
• Develop curated business-ready metrics to support analytics, dashboards, and AI/ML models.
• Design and manage a curated data layer with consistent metrics and definitions.
• Create and maintain executive dashboards for insights.
• Implement a data catalog to improve data discoverability and lineage.

Skills

Python programming

SQL

Data modeling

Cross-functional collaboration

Data governance

Education

Bachelor's degree in computer science, engineering, information systems, or related field

Master’s degree (preferred)

Tools

Google BigQuery

Dataflow

Dataform

Looker

Power BI

Tableau

Dash

REST APIs

CI/CD pipelines

Airflow/Composer

Job description

Ford Motor Company is hiring a Sr. Specialist focused on Yield Management GTM Data Engineering, responsible for end-to-end data solutions and business-ready metrics that support analytics, BI dashboards, and decision-making. The role spans data engineering, business intelligence, data science, and data governance, with close collaboration across cross-functional stakeholders.

Key Responsibilities

• 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 support internal advanced analytics and AI/ML models, dashboards, and other data consumers.
• Design and manage a curated data layer that converts raw datasets into consistent, business-friendly metrics and definitions.
• Design, build, and manage business-friendly dashboards used by executive leadership for business insights.
• Implement and maintain a data catalog or knowledge catalog (for example, Google Data Catalog) to improve data discoverability, lineage tracking, and metadata management.
• Optimize BigQuery performance using partitioning, clustering, query tuning, and cost-management best practices.
• Build and maintain data quality checks, monitoring, and alerting to support pipeline reliability and data trustworthiness.
• Partner with cross-functional teams (analytics, product, and business) to gather requirements and translate them into scalable data models and metrics.
• Enforce data governance, security, and access control standards, including PII handling, role-based access, and encryption.
• Write clean, well-tested, and maintainable code using Python and SQL, including backend frameworks for API-based ingestion routines.
• Create and maintain CI/CD pipelines to support deployments and change review across the code base.
• Participate in code reviews and architecture discussions, including CI/CD pipeline development for data and application deployments.

Required Qualifications

• Bachelor’s degree in computer science, engineering, information systems, or a related field (or a foreign equivalency), or an equivalent combination of relevant education and experience.
• 5+ years of experience in data engineering, software engineering, or a full-stack data role.
• 3+ years demonstrating strong programming skills in Python, SQL, Google BigQuery, and Dataflow.
• 3 years of hands-on experience with Google BigQuery and Dataform, including data modeling, query optimization, cost management, and scheduled queries.
• 3 years of practical experience building and maintaining a data mart to standardize business metrics.
• 2+ years of experience using business intelligence tools such as Looker, Power BI, Tableau, or custom apps built using Dash.
• 2+ years of proven experience designing and building ingestion routines based on APIs (REST).
• 2+ years of experience in roles requiring strong understanding of testing, monitoring, reliability, and maintainable software design.

Technologies

• Python, SQL
• Google BigQuery, ETL/ELT
• Google Data Catalog
• BigQuery partitioning, BigQuery clustering
• Dataform
• Google Dataflow
• Looker, Power BI, Tableau, Dash
• REST APIs
• CI/CD pipelines
• CI/CD

Benefits

• Immediate medical, dental, vision, and prescription drug coverage.
• Flexible family care days, paid parental leave, new parent ramp-up programs, and subsidized back-up child care.
• 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.
• Paid time off for paid holidays, including the week between Christmas and New Year’s Day.
• Paid time off and the option to purchase additional vacation time.

Preferred Qualifications (If You Have Them)

• Master’s degree in computer science, engineering, information systems, or a related field.
• Experience using AI to build or maintain code and pipelines.
• Ability to document data flows, API specifications, metric definitions, and system architecture for internal and cross-team use.
• Experience with a data catalog or metadata management tool (for example, Google Data Catalog) including lineage, tagging, and governance workflows.
• Strong SQL skills and experience with Python for data pipeline development and automation.
• Experience with cloud platforms, preferably Google Cloud Platform (GCP) (Cloud Storage, Cloud Functions, Dataflow, Pub/Sub, Composer/Airflow).
• Solid understanding of data modeling concepts (dimensional modeling, star or snowflake schemas, normalization).
• Familiarity with version control (Git) and CI/CD practices for data and application deployments.
• Strong understanding of data governance, security, and privacy best practices.
• Experience with orchestration tools such as Apache Airflow or Cloud Composer.
• Experience in the automotive, manufacturing, or connected vehicle data domain.
• Knowledge of BI and visualization tools (Looker, Tableau, Power BI).

Location and Compensation

Location: Dearborn, MI (hybrid).

Compensation: USD 115,000 to 192,900 per year. This role is salary grade 8, and the final salary within the range is determined based on the candidate’s skills and experience, along with job scope, responsibility, and competitive market value.