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Data Engineer Jobs in Rochester, MI (NOW HIRING)

Senior Data Engineer

Auburn Hills, MI · On-site

$100K - $136K/yr

About the Role Join the Supply Chain AI Hub as a Senior Data Engineer helping turn AI ambition into reliable data foundations and delivery-ready assets. This role helps engage business, engineering ...

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

Data Engineer - Supply Chain

Auburn Hills, MI · On-site

$108K - $130K/yr

The Data Engineer plays a critical role in enabling this vision by designing, building, and operating enterprise-grade data pipelines and analytical data products that power advanced analytics ...

Senior Data Engineer

Auburn Hills, MI

$100K - $136K/yr

About the Role Join the Supply Chain AI Hub as a Senior Data Engineer helping turn AI ambition into reliable data foundations and delivery-ready assets. This role helps engage business, engineering ...

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

Azure & Snowflake Data Engineer

Troy, MI · On-site

$107K - $128K/yr

Azure Data Engineer (Snowflake & Azure Data Factory) Overview / Summary Apply your Azure and Snowflake data engineering experience to build scalable pipelines and modern data solutions in a ...

The Data Engineer plays a critical role in enabling this vision by designing, building, and operating enterprise-grade data pipelines and analytical data products that power advanced analytics ...

Azure & Snowflake Data Engineer

Troy, MI · On-site

$108K - $130K/yr

Azure Data Engineer (Snowflake & Azure Data Factory) Overview / Summary Apply your Azure and Snowflake data engineering experience to build scalable pipelines and modern data solutions in a ...

Senior Data Engineer

Troy, MI · On-site +1

$100K - $136K/yr

About the Role As a hands-on Senior Data Engineer on a small team, you will build and scale the data platform driving Protera's clinical operations, payer reporting, and analytics. This is a senior ...

Senior Data Engineer

Detroit, MI · On-site

$104K - $142K/yr

As a Senior Data Engineer, you'll engage in the design, development, and maintenance of data platforms and solutions. This includes applying data management principles to pipelines and delivering ...

Senior Data Engineer

Detroit, MI

$104K - $142K/yr

As a Senior Data Engineer, you'll engage in the design, development, and maintenance of data platforms and solutions. This includes applying data management principles to pipelines and delivering ...

FULL-STACK DATA ENGINEER at MOTOR INFORMATION SYSTEMS MOTOR Information Systems, an operating group of Hearst, is actively seeking a Full-Stack Data Engineer. Ideally, a hands-on data engineer who ...

FULL-STACK DATA ENGINEER at MOTOR INFORMATION SYSTEMS MOTOR Information Systems, an operating group of Hearst, is actively seeking a Full-Stack Data Engineer. Ideally, a hands-on data engineer who ...

Showing results 21-40

Data Engineer information

See Rochester, MI salary details

$41K

$119.4K

$163.4K

How much do data engineer jobs pay per year?

As of Aug 19, 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.

What is a data engineer?

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.

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.

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 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.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.

What are the most commonly searched types of Data Engineer jobs in Rochester, MI?

The most popular types of Data Engineer jobs in Rochester, MI are:

What are popular job titles related to Data Engineer jobs in Rochester, MI?

For Data Engineer jobs in Rochester, MI, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in Rochester, MI look for?

The top searched job categories for Data Engineer jobs in Rochester, MI are:

What cities near Rochester, MI are hiring for Data Engineer jobs?

Cities near Rochester, MI with the most Data Engineer job openings:

Infographic showing various Data Engineer job openings in Rochester, MI as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $119,398 per year, or $57.4 per hour.

Senior Data Engineer

Stellantis

Auburn Hills, MI • On-site

$100K - $136K/yr

Full-time

Re-posted 6 days ago


Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

14th of 44 rated automakers


Job description

About the Role
Join the Supply Chain AI Hub as a Senior Data Engineer helping turn AI ambition into reliable data foundations and delivery-ready assets. This role helps engage business, engineering and ICT stakeholders around practical data needs and constraints, scale AI delivery through stronger data models, pipelines, integration pathways, quality routines and traceability, and pioneer more robust data-engineering practices that make solutions easier to trust, operate and industrialize.
Your Missions:
Data Modelling, Pipelines & Reuse:
  • Design, improve or govern selected data models, transformation logic and pipeline components that support AI and analytics use cases
  • Promote maintainable structures, reusable components and clear lineage across transformations where relevant
  • Support delivery teams with practical data-engineering discipline rather than one-off technical builds

Platform, Integration & Traceability:
  • Clarify selected source-to-platform pathways, integration dependencies and technical constraints affecting delivery
  • Help maintain visibility on traceability, handoffs and access conditions across Supply Chain
  • Work with ICT and engineering stakeholders to keep the build path practical and scalable

Data Quality, Certification & Governance Support:
  • Contribute to selected quality checks, certification routines, governance expectations or compliance-related traceability needs depending on the scope assigned
  • Help surface structural data issues, documentation gaps or control weaknesses that affect deployment readiness
  • Support a trusted delivery environment by making data assets more visible, understandable and supportable

Your Profile:
  • Strong data-engineering experience in modern enterprise environments, with depth in some combination of data modelling, pipelines, integration, quality, lineage or governance-related topics
  • Able to operate across business needs, technical constraints and delivery realities
  • Strong SQL and practical understanding of data structures, transformations, traceability and controlled delivery environments
  • Comfortable working with multiple stakeholders across architecture, data, engineering and governance topics
  • Structured, pragmatic and able to take ownership of a defined subset of a broader senior data-engineering scope

Skills You'll Grow:
  • Broader exposure across the different building blocks that make AI-ready data operational at scale
  • Experience working at the intersection of data engineering, integration, quality and delivery governance
  • Opportunity to deepen expertise in a specific component while contributing to a wider AI data foundation agenda

Why Join / Impact:
  • Work on data-engineering challenges directly tied to real AI deployment in Supply Chain
  • Join a role broad enough to offer variety, while still allowing focused ownership on a defined perimeter
  • Help strengthen the data foundations that make scalable AI delivery possible

Basic Qualifications:
  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, Engineering, Mathematics, or related field
  • 8 years of experience in data engineering or data platforms
  • Previous Supply Chain experience
  • Hands-on experience with modern data platforms such as Databricks, Spark, Snowflake, or equivalent
  • Experience with data pipelines, integration, semantic, lineage, architecture and platform environments
  • Enterprise-scale data transformation and delivery experience
  • Ability to collaborate effectively with analytics, AI, and software engineering teams

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