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Manager Data Engineering Jobs in Detroit, MI (NOW HIRING)

Data Engineer

Auburn Hills, MI

$108K - $130K/yr

The ideal candidate combines strong project management discipline with technical fluency and an understanding of automotive cost engineering, finance and purchasing data. You will manage end-to-end ...

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Data engineering, data product development and software product launches * At least three of the ... Relational Database Management System like MySQL, PostgreSQL, and SQL Server. * Real-Time data ...

In data engineering at PwC, you will focus on designing and building data infrastructure and ... As a Senior Manager you lead large projects, innovate processes, and maintain operational ...

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Data engineering, data product development and software product launches * At least three of the ... Relational Database Management System like MySQL, PostgreSQL, and SQL Server. * Real-Time data ...

Data Engineer

Dearborn, MI

$105K - $127K/yr

Project management tools like Atlassian JIRA. Even better if you have... * Ph.D. or foreign equivalent degree in Computer Science, Software Engineering, Information System, Data Engineering, or a ...

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Develops and supports MLOps workflows, including model tracking, versioning, and lifecycle management using MLflow * Builds and maintains CI/CD pipelines for both data engineering and machine ...

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Develops and supports MLOps workflows, including model tracking, versioning, and lifecycle management using MLflow * Builds and maintains CI/CD pipelines for both data engineering and machine ...

Data Engineer

Auburn Hills, MI

$108K - $130K/yr

Develops and supports MLOps workflows, including model tracking, versioning, and lifecycle management using MLflow * Builds and maintains CI/CD pipelines for both data engineering and machine ...

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Hands-on experience with Terraform for infrastructure management and GitHub Actions for CI/CD pipelines. * Software Engineering Foundation: Solid understanding of data structures, algorithms, and ...

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Hands-on experience with Terraform for infrastructure management and GitHub Actions for CI/CD pipelines. • Software Engineering Foundation: Solid understanding of data structures, algorithms, and ...

Showing results 41-60

Manager Data Engineering information

See Detroit, MI salary details

$30.7K

$96.2K

$170.3K

How much do manager data engineering jobs pay per year?

As of Aug 18, 2026, the average yearly pay for manager data engineering in Detroit, MI is $96,170.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,300.00 and $124,200.00 per year, depending on experience, location, and employer.

What are the roles and responsibilities of a manager data engineering?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

What are the key skills and qualifications needed to thrive as a manager data engineering?

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

How does a manager data engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.

What is the difference between Manager Data Engineering vs Data Engineer?

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the most commonly searched types of Data Engineering jobs in Detroit, MI?

The most popular types of Data Engineering jobs in Detroit, MI are:

What are popular job titles related to Manager Data Engineering jobs in Detroit, MI?

For Manager Data Engineering jobs in Detroit, MI, the most frequently searched job titles are:

What cities near Detroit, MI are hiring for Manager Data Engineering jobs?

Cities near Detroit, MI with the most Manager Data Engineering job openings:

Infographic showing various Manager Data Engineering job openings in Detroit, MI as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $96,170 per year, or $46.2 per hour.

Senior Data Solutions Architect (AWS, Big Data, Data Engineering)

FCA

Auburn Hills, MI • On-site

$63.75 - $85.25/hr

Other

Re-posted yesterday


Job description


Build the Future of Connected Vehicle Data at Stellantis
Stellantis is transforming the future of mobility through connected vehicles, advanced
analytics, artificial intelligence, and data-driven products. Our AI & Data Analytics team
develops scalable platforms and innovative data solutions that power some of the world's
most recognized automotive brands.
We are seeking a Senior Data Solutions Architect to lead the design and implementation of
enterprise-scale data products and platforms. This role combines technical leadership,
architecture, cloud engineering, and stakeholder collaboration to deliver secure, scalable,
and high-performance data solutions that support both internal software products and
external customer offerings.
If you are passionate about cloud architecture, big data technologies, real-time data
processing, and building modern data platforms from the ground up, we'd like to hear from
you.
About the Role
As a Senior Data Solutions Architect, you will serve as a technical leader responsible for
defining architecture, driving technology decisions, and building scalable data services
that support Stellantis' connected vehicle ecosystem.
You will be a partner with engineering, product, analytics, and business teams to develop
modern cloud-based data platforms, establish engineering best practices, and ensure
data quality across the organization.
This role requires expertise in data architecture, cloud technologies, and distributed
processing systems, real-time data pipelines, and large-scale data engineering.
What You'll Do
Data Architecture & Solution Design
* Lead the architecture and technical design of enterprise data solutions for internal
* platforms and customer-facing products.
* Design and implement secure, scalable, resilient, and high-performance data
* services using modern cloud and Big Data technologies.
* Define architecture standards and engineering best practices for data platforms
* and analytics solutions.
* Evaluate technology options and make architecture decisions that align with
* business and technical objectives.
Cloud & Big Data Engineering
* Design and implement distributed data processing solutions using cloud-native
* technologies.
* Build scalable data pipelines for ingestion, transformation, validation, and delivery
* of connected vehicle data.
* Develop real-time and batch processing architectures that support growing
* business needs.
* Ensure data platforms meet performance, reliability, scalability, and security
* requirements.
Technical Leadership
* Provide technical direction across multiple engineering teams.
* Influence architectural decisions and drive alignment across cross-functional organizations.
* Lead implementation efforts from concept through production deployment.
* Mentor and support engineers and technical team members to help grow organizational capabilities.
Data Quality & Operational Excellence
* Establish and maintain data quality standards, validation processes, and
* monitoring frameworks.
* Lead efforts to standardize instrumentation, observability, and operational
* readiness across software platforms.
* Develop comprehensive documentation, runbooks, and troubleshooting
* processes.
* Drive continuous improvement initiatives across data engineering and platform operations.
Stakeholder Collaboration
* Partner with product, engineering, analytics, and business teams to understand
* complex requirements and deliver effective solutions.
* Build strong relationships with upstream and downstream stakeholders to ensure
* successful delivery of data products.
* Translate technical concepts into clear business outcomes and recommendations.
Basic Qualifications:
* Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline.
* A minimum of 8 years of experience in data engineering, software development, or data platform architecture. Including:
* A minimum of 4 years of hands-on experience building and maintaining production-grade data applications.
* A minimum of 4 years of experience working with AWS cloud services in production environments.
* Experience designing and implementing enterprise-scale data solutions and platforms.
* Data architecture and data modeling
* Relational and columnar database technologies
* Operational data stores
* Master data management
* ETL and ELT design, implementation, and optimization
* Data quality management and validation frameworks
* AWS cloud services
* Apache Spark
* Distributed data processing platforms
* Python
* Java
* Notification Event Bus
* Kinesis
* SNS (Simply Notification Service)
* SQS (Simple Queue Service)
* MQ (Message Queue)
* Apache Airflow
* Azure Data Factory
* Workflow orchestration platforms
* API design and development
* Data service architecture
* Integration patterns and distributed systems
* Experience leading cross-functional technical initiatives.
* Ability to architect solutions from concept through implementation.
* Strong communication skills with the ability to translate complex technical concepts into business-focused solutions.
* Experience mentoring and guiding engineering teams.
Preferred Qualifications:
* AWS certification or equivalent cloud certification.
* Experience with Databricks and Databricks notebook workflows.
* Experience with Infrastructure as Code (IaC) tools such as Terraform.
* Experience supporting enterprise analytics, machine learning, or AI-driven platforms.
* Experience working with connected vehicle, IoT, or large-scale telemetry data