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Data Engineer Jobs in Rochester, MI (NOW HIRING)

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Cost Methods, Tools & Data Solutions (CMTD) is seeking a Data Engineer , preferably with a finance or cost engineering background and hands-on exposure to data engineering to drive delivery of modern ...

General Motors

Data Engineer

Warren, MI · On-site

$107K - $129K/yr

You will partner closely with product owners, architects, data engineers, report and analytics teams, and source-system teams to define trusted data products, improve data quality and reliability ...

HTC Global Services

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Associate Data Engineer - Voice of the Customer Analytics Position Overview The Associate Data Engineer will support data engineering, analytics, and reporting initiatives for Voice of the Customer ...

New

Continental Services

Data Engineer

Sterling Heights, MI · On-site

$107K - $128K/yr

Data Engineer Department: Information Technology 500003 Employment Type: Full Time Location: Sterling Heights Reporting To: Matt Knutson Description A Taste of Who We Are: Backed by a tireless ...

Continental Services

Data Engineer

Sterling Heights, MI · On-site

$97K - $146K/yr

The Data Engineer is a hands-on technical contributor who plays a foundational role in building the data infrastructure that powers Continental's analytics, reporting, and AI initiatives. This person ...

Epitec

Data Engineer

Southfield, MI · On-site

$114K/yr

Data Engineer (Job Code: 1391) Duties : Responsible for supporting vehicle feature level performance sign-offs through data exploration and analysis of data collected from real-world evaluation ...

Continental Services

Data Engineer

Sterling Heights, MI · On-site

$106K - $128K/yr

The Data Engineer is a hands-on technical contributor who plays a foundational role in building the data infrastructure that powers Continental's analytics, reporting, and AI initiatives. This person ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Role Overview We are looking for a DevOps / Data Engineer to build and manage scalable cloud infrastructure, CI/CD pipelines, and data workflows on AWS. This role combines DevOps, automation, and ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that process ...

Horizontal Talent

Data Engineer

Sterling Heights, MI · On-site +1

$106K - $128K/yr

Join our innovative team as a Data Engineer/Scientist, where you'll have the opportunity to design and maintain cutting-edge data infrastructure, ensuring seamless data accessibility for various ...

New

Bright Mind Solutions LLC

Data Engineer

Warren, MI · On-site

$45 - $50/hr

The Data Engineer handles leading and delivering new and innovative data driven solutions that are elegant and professional. You will work closely with our forward-thinking Data Scientists, BI ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$113K - $135K/yr

Role Overview We are looking for a DevOps / Data Engineer to build and manage scalable cloud infrastructure, CI/CD pipelines, and data workflows on AWS. This role combines DevOps, automation, and ...

Bright Mind Solutions LLC

Data Engineer

Warren, MI · On-site

$45 - $50/hr

The Data Engineer handles leading and delivering new and innovative data driven solutions that are elegant and professional. You will work closely with our forward-thinking Data Scientists, BI ...

Contact Government Services, LLC

Data Engineer

Detroit, MI · On-site

$113K - $136K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is seeking a passionate and driven Data Engineer to support a rapidly growing Data Analytics and Business ...

Deloitte

Databricks Data Engineer

Detroit, MI · On-site

$113K - $136K/yr

As a Databricks Data Engineer, you will support the design, build, and optimization of cloud-based data engineering solutions that enable large-scale transformation. You will work with business and ...

Contact Government Services, LLC

Data Engineer

Detroit, MI

$113K - $136K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is seeking a passionate and driven Data Engineer to support a rapidly growing Data Analytics and Business ...

Mobilisights Connect

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

The Data Engineer will design and build a scalable data platform, implement low latency streaming data pipelines, and ensure operational excellence through monitoring and troubleshooting.

Stellantis

ICT Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Data engineering is the practice of making the appropriate data available to various data consumers (including data scientists, data and business analysts, citizen integrators, and line-of-business ...

New

Bespoke Labs

Data Engineer

Rochester Hills, MI · On-site

$105K - $126K/yr

Must-Have Skills 3+ years of data engineering experience -- pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools ...

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All JobsData Engineer JobsData Engineer Jobs in Rochester, MI

Data Engineer information

See Rochester, MI salary details

$41K

$119.4K

$163.4K

How much do data engineer jobs pay per year?

As of Jul 8, 2026, the average yearly pay for data engineer in Rochester, MI is $119,398.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,400.00 and $126,600.00 per year, depending on experience, location, and employer.

Is a data engineer a difficult job?

A data engineer role involves designing, building, and maintaining data pipelines and infrastructure, which requires strong programming skills, knowledge of databases, and familiarity with tools like SQL, Python, and cloud platforms. The job can be challenging due to the complexity of managing large-scale data systems and ensuring data quality and security, but it is manageable with proper training and experience.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

What are the key skills and qualifications needed to thrive as a Data Engineer, and why are they important?

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What Does a Data Engineer Do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What are Data Engineers?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do Data Engineers typically collaborate with Data Scientists and Analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipelines. Entry-level positions may be available for those with relevant internships, certifications, or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect prior experience or demonstrated technical competence.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and certifications can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, and other incentives. These roles typically require strong programming, cloud platform expertise, and a deep understanding of data architecture.
More about Data Engineer jobs
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Data Engineer jobs near you
Data Engineer

Data Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 5 days ago

Stellantis rating

7.4

Company rating: 7.4 out of 10

Based on 126 frontline employees who took The Breakroom Quiz

17th of 44 rated automakers

Job description

Cost Methods, Tools & Data Solutions (CMTD) is seeking a Data Engineer, preferably with a finance or cost engineering background and hands-on exposure to data engineering to drive delivery of modern analytics, automation and AI-enabled solutions. This role will lead cross-functional initiatives spanning cloud data platforms (Snowflake/AWS/Azure), Databricks, Palantir Foundry, and the Microsoft Power Platform (Power Apps, Power Automate, Power BI, Dataverse). 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 project execution, while working closely with business and ICT partners to deliver scalable, secure, and high-impact data products. Experience with agentic AI chatbot development and Generative AI / Microsoft Copilot is strongly preferred.
Basic Qualifications:
  • Bachelor's degree in Computer Science (or a related technical field.).
  • 3+ years of professional experience technical project delivery, data engineering, or analytics platform implementation.
  • Demonstrated project management skills: planning, execution, stakeholder management, risk management, and delivery governance.
  • Finance or costing background, with understanding of cost drivers, financial models, or cost engineering processes.
  • Data engineering exposure: pipelines, transformations, data modeling concepts, and working with data engineering teams.
  • Experience with one or more cloud database environments such as Snowflake, AWS, or Azure.
  • Hands-on development and experience with one or more of the following:
  • Snowflake, AWS, or Azure
  • Databricks
  • Palantir Foundry
  • SQL
  • Microsoft Power Platform (Power Apps, Power Automate, Power BI, Dataverse)

Preferred Qualifications:
  • Automotive industry experience, particularly in cost engineering, manufacturing, or product development.
  • Experience with agentic AI chatbot development or internal AI assistants.
  • Knowledge of Generative AI and familiarity with Microsoft Copilot capabilities and adoption strategies.
  • Experience with enterprise governance for analytics platforms.
  • Familiarity with Agile delivery (Scrum/Kanban), DevOps concepts, and structured release management.

Skills & Competencies:
  • Strong communication skills: ability to explain technical details to non-technical stakeholders and align decisions quickly.
  • Highly organized with strong attention to detail; effective at managing ambiguity and changing priorities.
  • Ability to influence across teams without direct authority; strong facilitation and conflict resolution skills.
  • Analytical mindset with comfort interpreting data issues (reconciliation, validation, root cause analysis).
  • Customer-focused approach: understands end-user workflow pain points and drives practical, adoptable solutions.
  • Passion for digital transformation, automation, and AI-driven solutions.

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