# Manager, Data Engineering

**Company**: Ford Motor Company
**Location**: Dearborn
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: Competitive salary and benefits package
**Category**: Engineering
**Industry**: Automotive
**Wikidata**: https://www.wikidata.org/wiki/Q44294

**Apply**: https://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/62339
**Canonical**: https://yubhub.co/jobs/job_eb99c035-971

## Description

We're looking for a seasoned Data Engineering Manager to lead our team in designing, developing, and maintaining data pipelines that support our Data Hub strategy. As a key member of our Global Data Insight & Analytics team, you'll be responsible for building and maintaining data assets and services that empower Artificial Intelligence, Data Science, and Software Engineering.

Responsibilities:

- Lead a high-performing team of Portfolio Data Engineers, fostering a culture of collaboration, innovation, and continuous improvement.

- Strategically prioritize and manage team workloads, ensuring effective task allocation and resource capacity to support team goals.

- Provide expert technical guidance and mentorship, ensuring adherence to best practices, coding standards, and architectural guidelines.

- Act as the Chief Data Technical Anchor for the PLMA domain, resolving critical incidents through Root Cause Analysis (RCA) and implementing permanent, resilient architectural fixes.

- Oversee the design, development, maintenance, scalability, reliability, and performance of data platform pipelines, aligning them with business needs and strategic objectives.

- Contribute to the long-term strategic direction of the Data Platform by proactively identifying opportunities for best practice adoption and standardization.

- Champion data quality, governance, and security standards, ensuring compliance and safeguarding sensitive data assets.

- Enhance efficiency and reduce redundancy by consolidating common tasks across teams.

- Effectively communicate decisions to stakeholders, building strong relationships and ensuring alignment on data initiatives.

- Maintain awareness of industry trends and emerging technologies to inform technical decisions.

- Lead the implementation of customer requests into data assets, ensuring optimized design and code development.

- Guide the team in delivering scalable, robust data solutions and contribute hands-on to critical projects, including design and code reviews.

- Lead technical decisions that drive data innovation and resilience.

- Demonstrate full stack cloud data engineering expertise, covering automation, versioning, ingestion, integration, transformation, optimization, and data modeling.

- Engage in agile planning, including scope, work breakdown structure, as well as roadblock resolution.

- Design solutions for cost and consumption optimization, scalability, and performance.

- Collaborate with Data Architecture and stakeholders on solution design, data consolidation, retention, purpose of use, compliance, and audit requirements.

- Drive engineering excellence by establishing and monitoring SWE-centric quality metrics (including DORA metrics and P99 latency targets).

Requirements:

- Bachelor's degree in Computer Science, Information Technology, Information Systems, Data Analytics, or a related field.

- 8+ years of experience in complex data environments, demonstrating increased responsibilities and achievements with:

+ Expertise in programming languages such as Python or Scala, and strong SQL skills. 	+ Experience with ETL/ELT processes, data warehousing, and data modeling. 	+ Experience with CI/CD pipelines, Docker, Git/Gerrit, and experience designing resilient deployment strategies and sophisticated release management. 	+ Familiarity of data governance, privacy, quality, and monitoring.

- Proven experience in implementing sophisticated testing strategies, driving quality tool adoption, establishing comprehensive code review processes, and setting observability standards with advanced monitoring and proactive alerting.

- 5+ years of experience within the automotive industry or related product development environments and product lifecycle management.

- 5+ years of experience in leading software or data engineering teams, with a focus on team development and project success.

- 5+ years of experience in Big Data environments or expertise with Big Data tools, including:

+ Data processing frameworks and data modeling. 	+ In-depth knowledge and practical experience with Google Cloud Platform services. 	+ Proven experience in monitoring and optimizing costs and compute resources in hyperscaler platforms.

- Significant experience leveraging Generative AI and LLMs to optimize data engineering workflows (e.g., automated code generation, documentation, or metadata management).

Preferred Qualifications:

- Master's degree in Computer Science, Engineering, or a related field.

- Expertise in GCP based data engineering services like BQ, Dataflow, Airflow, Dataform, Datastream, Apache Beam, Cloud Run, Cloud Functions

- Familiarity with automotive Product Development processes, including program planning, design validation, and cross-functional collaboration across engineering, manufacturing, and supplier teams to deliver data-driven insights at each lifecycle stage

- Experience in managing and scaling serverless applications and clusters, focusing on resource optimization and robust monitoring and logging strategies.

- Proficiency in unstructured data ingestion, including experience with data modeling and preparation techniques to support AI and machine learning workloads.

- Experience with AI architecture and AI enabling tech (graph database, vector database, etc)

- Familiarity with data visualization tools (e.g., Power BI, Tableau).

- Working knowledge of ontology, semantic modeling, and related technologies

## Skills

### Required
- Python
- Scala
- SQL
- ETL/ELT processes
- data warehousing
- data modeling
- CI/CD pipelines
- Docker
- Git/Gerrit
- data governance
- privacy
- quality
- monitoring

### Nice to have
- Generative AI
- LLMs
- GCP based data engineering services
- BQ
- Dataflow
- Airflow
- Dataform
- Datastream
- Apache Beam
- Cloud Run
- Cloud Functions
- automotive Product Development processes
- program planning
- design validation
- cross-functional collaboration
- data-driven insights
- unstructured data ingestion
- preparation techniques
- AI architecture
- AI enabling tech
- graph database
- vector database
- data visualization tools
- ontology
- semantic modeling