Data Engineering Manager Jobs
Data Engineering Manager jobs are open across fintech, healthtech, e-commerce, and enterprise software, from senior individual contributor to director and VP, with specializations in cloud infrastructure, real-time pipelines, and platform engineering. Find a role that fits from the openings below and apply directly.
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Overview
At Ford, you’ll work on ideas that matter, alongside passionate people who want to make a global impact. Together, we’re shaping the next era of transportation—grounded in purpose, driven by progress. Make your move.
- Job Type: Full time
- Work Type: Hybrid
PRO 360 requires a Data Engineering Manager to design, develop, and maintain the enterprise data architecture that unifies commercial customer data across Vehicles, Service, Software, and Ford Credit.
- Lead Data Engineering: Drive the development of real-time and batch data pipelines, manage GCP infrastructure, ensure code quality, and oversee integrations with downstream systems like Salesforce and Marketing Cloud.
- Drive AI Data Initiatives: Architect data foundations to support AI monetization, including predictive analytics and cutting-edge Agentic AI workflows leveraging Google Vertex AI and Gemini.
- Enforce Data Governance: Implement "Policy as Code," machine-readable data contracts, data quality observability, and strict privacy controls (GDPR, CCPA, PRO ID management).
Why This Role Matters As the definitive source of truth for Ford Pro’s commercial customers, PRO 360 is the engine behind Ford Pro’s growth and efficiency goals. This LL6 leadership role ensures that our data is scalable, AI-ready, and highly governed—directly enabling Ford Pro’s commercial success.
Job Responsibilities
Data Engineering:
- Lead Engineering Execution: Manage and mentor pods of data and software engineers to design, build, and deploy domain-driven data products on Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Composer/Airflow).
- Platform Modernization: Drive critical infrastructure initiatives, including the migration to GCP 3.0, adoption of DataOps packages, and the decommissioning of legacy tech debt to ensure highly performant and cost-optimized cloud operations.
- Ecosystem Integration: Architect real-time and batch data pipelines to ingest fragmented data and serve unified profiles to downstream operational systems, specifically Salesforce (Sales/Service Cloud), Marketing Cloud, and Ford Credit billing systems.
- Engineering Craftsmanship: Enforce rigorous engineering standards, ensuring 100% of PRO 360 repositories maintain SonarQube "A" ratings for reliability, security, and maintainability, and championing CI/CD automation.
- Technical Leadership: Act as the Directly Responsible Individual (DRI) for technical deployments, collaborating with Product Managers and Product Anchors to translate business OKRs into scalable technical backlogs.
AI Initiatives:
- AI Data Readiness: Architect and optimize data models to support high-priority machine learning initiatives ensuring training and inference pipelines are highly available and scalable.
- Agentic AI Enablement: Lead the data integration strategy for next-generation Agentic AI workflows (using Vertex AI, Gemini, and Agent Platforms), enabling autonomous lead generation, pipeline observability, and conversational AI dashboards.
- Feature Engineering & ML Ops: Collaborate closely with Data Scientists and AI Engineers to transition ML models from proof-of-concept to production, ensuring seamless integration into the PRO 360 ecosystem.
- Unstructured Data & RAG: Build pipelines to process and structure complex datasets (e.g., telematics, connected vehicle data, unstructured web leads) to feed into Large Language Models and Retrieval-Augmented Generation (RAG) frameworks.
Data Governance, Quality & Compliance:
- Data Contracts & Observability: Implement machine-readable data contracts (Schema, SLOs, and DQ rules) for top PRO 360 data products. Oversee automated data quality monitoring and anomaly detection using platform observability tools.
- Privacy & Compliance Controls: Architect and develop automated governance controls to map data assets to privacy classifications. Ensure strict adherence to GDPR and CCPA, including the automated management and suppression/deletion of consent data.
- Policy as Code: Translate business and regulatory policies into enforceable, automated standards within the CI/CD pipeline, eliminating manual configuration errors.
- Federated Data Sharing: Manage the governance of sharing PRO 360 data with internal pillars (FCSD, FPI, FMCC) and external partners (e.g., D&B, S&P) through secure, role-based, and attribute-based access controls.
Bachelor’s / Masters’s Degree in Computer Science, Data Engineering, Information Technology, or a related technical field.
Required Qualifications
- 10+ years of hands-on experience in Data Engineering, Data Architecture, or AI/ML Ops, with 3+ years in a technical leadership.
- Deep technical proficiency in Google Cloud Platform (GCP) data services, including BigQuery, Cloud Composer, Dataflow, Pub/Sub, and Dataplex.
- Proven track record of operationalizing AI/ML models and supporting GenAI/Agentic AI infrastructure (Vertex AI, LLM orchestration).
- Strong programming skills in Python and SQL, with proficiency in Terraform/IaC for infrastructure automation.
- Experience building and scaling Customer Data Platforms (CDPs), Master Data Management (MDM) solutions, or complex B2B data ecosystems.
- Familiarity with CRM integrations (specifically Salesforce) and enterprise billing/financial data flows.
- Strong understanding of enterprise data governance, data contracts, and global privacy regulations (GDPR, CCPA).
- Excellent communication skills with the ability to translate complex technical architectures to business stakeholders and executive leadership.
You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
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 child care 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.
This position is leadership level 6 and ranges from $132,800-$250,800.
Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.
Visa sponsorship is available for this position.
Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.
This position is hybrid. Candidates who are in commuting distance to a Ford hub location may be required to be onsite four or more days per week.
LI-Hybrid
LI-GR1
Overview
At Ford, you’ll work on ideas that matter, alongside passionate people who want to make a global impact. Together, we’re shaping the next era of transportation—grounded in purpose, driven by progress. Make your move.
- Job Type: Full time
- Work Type: Hybrid
PRO 360 requires a Data Engineering Manager to design, develop, and maintain the enterprise data architecture that unifies commercial customer data across Vehicles, Service, Software, and Ford Credit.
- Lead Data Engineering: Drive the development of real-time and batch data pipelines, manage GCP infrastructure, ensure code quality, and oversee integrations with downstream systems like Salesforce and Marketing Cloud.
- Drive AI Data Initiatives: Architect data foundations to support AI monetization, including predictive analytics and cutting-edge Agentic AI workflows leveraging Google Vertex AI and Gemini.
- Enforce Data Governance: Implement "Policy as Code," machine-readable data contracts, data quality observability, and strict privacy controls (GDPR, CCPA, PRO ID management).
Why This Role Matters As the definitive source of truth for Ford Pro’s commercial customers, PRO 360 is the engine behind Ford Pro’s growth and efficiency goals. This LL6 leadership role ensures that our data is scalable, AI-ready, and highly governed—directly enabling Ford Pro’s commercial success.
Job Responsibilities
Data Engineering:
- Lead Engineering Execution: Manage and mentor pods of data and software engineers to design, build, and deploy domain-driven data products on Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Composer/Airflow).
- Platform Modernization: Drive critical infrastructure initiatives, including the migration to GCP 3.0, adoption of DataOps packages, and the decommissioning of legacy tech debt to ensure highly performant and cost-optimized cloud operations.
- Ecosystem Integration: Architect real-time and batch data pipelines to ingest fragmented data and serve unified profiles to downstream operational systems, specifically Salesforce (Sales/Service Cloud), Marketing Cloud, and Ford Credit billing systems.
- Engineering Craftsmanship: Enforce rigorous engineering standards, ensuring 100% of PRO 360 repositories maintain SonarQube "A" ratings for reliability, security, and maintainability, and championing CI/CD automation.
- Technical Leadership: Act as the Directly Responsible Individual (DRI) for technical deployments, collaborating with Product Managers and Product Anchors to translate business OKRs into scalable technical backlogs.
AI Initiatives:
- AI Data Readiness: Architect and optimize data models to support high-priority machine learning initiatives ensuring training and inference pipelines are highly available and scalable.
- Agentic AI Enablement: Lead the data integration strategy for next-generation Agentic AI workflows (using Vertex AI, Gemini, and Agent Platforms), enabling autonomous lead generation, pipeline observability, and conversational AI dashboards.
- Feature Engineering & ML Ops: Collaborate closely with Data Scientists and AI Engineers to transition ML models from proof-of-concept to production, ensuring seamless integration into the PRO 360 ecosystem.
- Unstructured Data & RAG: Build pipelines to process and structure complex datasets (e.g., telematics, connected vehicle data, unstructured web leads) to feed into Large Language Models and Retrieval-Augmented Generation (RAG) frameworks.
Data Governance, Quality & Compliance:
- Data Contracts & Observability: Implement machine-readable data contracts (Schema, SLOs, and DQ rules) for top PRO 360 data products. Oversee automated data quality monitoring and anomaly detection using platform observability tools.
- Privacy & Compliance Controls: Architect and develop automated governance controls to map data assets to privacy classifications. Ensure strict adherence to GDPR and CCPA, including the automated management and suppression/deletion of consent data.
- Policy as Code: Translate business and regulatory policies into enforceable, automated standards within the CI/CD pipeline, eliminating manual configuration errors.
- Federated Data Sharing: Manage the governance of sharing PRO 360 data with internal pillars (FCSD, FPI, FMCC) and external partners (e.g., D&B, S&P) through secure, role-based, and attribute-based access controls.
Bachelor’s / Masters’s Degree in Computer Science, Data Engineering, Information Technology, or a related technical field.
Required Qualifications
- 10+ years of hands-on experience in Data Engineering, Data Architecture, or AI/ML Ops, with 3+ years in a technical leadership.
- Deep technical proficiency in Google Cloud Platform (GCP) data services, including BigQuery, Cloud Composer, Dataflow, Pub/Sub, and Dataplex.
- Proven track record of operationalizing AI/ML models and supporting GenAI/Agentic AI infrastructure (Vertex AI, LLM orchestration).
- Strong programming skills in Python and SQL, with proficiency in Terraform/IaC for infrastructure automation.
- Experience building and scaling Customer Data Platforms (CDPs), Master Data Management (MDM) solutions, or complex B2B data ecosystems.
- Familiarity with CRM integrations (specifically Salesforce) and enterprise billing/financial data flows.
- Strong understanding of enterprise data governance, data contracts, and global privacy regulations (GDPR, CCPA).
- Excellent communication skills with the ability to translate complex technical architectures to business stakeholders and executive leadership.
You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
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 child care 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.
This position is leadership level 6 and ranges from $132,800-$250,800.
Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.
Visa sponsorship is available for this position.
Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.
This position is hybrid. Candidates who are in commuting distance to a Ford hub location may be required to be onsite four or more days per week.
LI-Hybrid
LI-GR1
See All 1,431+ Data Engineering Manager Jobs
Jump back to the full list of openings and apply to any data engineering manager role that fits.
Find Data Engineering Manager JobsData Engineering Manager Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Apple131
- Amazon96
- CVS Health64
- Google31
- Capital One30
Top Industries Hiring
- Technology & Software442
- Electronics & Hardware138
- Banking & Financial Services104
- Consulting & Professional Services96
- Healthcare & Medical Services82
What Employers Look For
The qualifications that appear most often in data engineering manager jobs.
- 5 or more years of experience in data engineering with at least 2 years in a management role
- Proficiency with cloud platforms such as AWS, GCP, or Azure and their managed data services
- Hands-on experience building and maintaining batch and streaming data pipelines at production scale
- Familiarity with modern data stack tools including dbt, Airflow, Spark, Kafka, or equivalent
- Experience with data warehousing solutions such as Snowflake, BigQuery, or Redshift
- Bachelor's degree in computer science, engineering, or a related technical field
Tips for Your Data Engineering Manager Job Search
Quantify pipeline scale on your resume
Hiring managers want to see the scope of what you've owned. Replace vague bullets with specifics: daily data volume processed, number of engineers managed, and latency improvements shipped. Data engineering manager resumes that lack those anchors read as generic.
Highlight architecture decisions, not just tools
Listings for this role screen for judgment, not just Spark or Kafka experience. Show where you chose one approach over another and why. Candidates who explain tradeoffs in their materials move faster through early screens than those who list tools alone.
Target listings that match your stack depth
Filter openings by the data platform your team has used most, whether that's Databricks, Snowflake, dbt, or a cloud-native stack. Applying where your hands-on depth aligns with the job description increases your callback rate more than applying broadly.
Apply early to roles that fit
Migrate Mate lists data engineering manager openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a cross-functional leadership story
Interviewers at this level probe how you work with data science, product, and platform teams, not just how you run your own squad. Have a concrete example ready where you aligned engineering priorities with a non-engineering stakeholder and delivered a measurable outcome.
Negotiate scope before negotiating anything else
In final-round conversations, clarify team size, on-call expectations, and technical debt load before discussing other terms. Data engineering manager roles vary widely in what 'manager' actually means, and misaligned scope is the top reason early attrition happens in this function.
Data Engineering Manager Jobs: Frequently Asked Questions
Which companies are hiring the most data engineering managers?
The companies hiring the most data engineering managers right now include Apple, Amazon, and CVS Health, with the largest share of openings in California, Texas, and New York, based on current listings on Migrate Mate as of June 2026. Demand is especially concentrated in companies scaling their analytics or AI infrastructure.
How many data engineering manager jobs are remote?
About 30% of data engineering manager openings are fully remote or hybrid as of June 2026, making this one of the more remote-accessible management roles in engineering. Platform engineering and cloud infrastructure sub-areas tend to have the highest share of fully distributed positions.
How do you become a data engineering manager?
Most data engineering managers start as senior data engineers, take ownership of project delivery, then step into informal team-lead responsibilities before moving into a formal manager title. The clearest path is building both deep pipeline expertise and a record of mentoring junior engineers, then seeking a team lead or staff-level role where you can demonstrate cross-functional coordination and hiring involvement.
Can you get hired as a data engineering manager with limited management experience?
Yes, particularly at startups and growth-stage companies where the first data engineering manager hire is often a strong senior engineer willing to grow into the role. The most effective approach is to surface any informal leadership experience, such as onboarding engineers, owning architecture decisions, or running incident reviews, and frame those in your resume and interviews as evidence of managerial readiness.
What does the data engineering manager interview process look like?
Most processes include a recruiter screen, a technical assessment covering pipeline design and system architecture, a people-management interview focused on team structure and conflict resolution, and a cross-functional panel with data science or product stakeholders. Final rounds often include a presentation where you propose an engineering roadmap or critique an existing data architecture, which tests both technical judgment and communication.
Where can I find and apply to data engineering manager jobs?
You can find and apply to data engineering manager jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your experience and stack, then apply directly to each listing from the page.
See All 1,431+ Data Engineering Manager Jobs
Jump back to the full list of openings and apply to any data engineering manager role that fits.
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