1

Data Engineer Jobs in Michigan (NOW HIRING)

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

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

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Data Engineer #1052627 * Employees in this job function are responsible for designing, building, and maintaining data solutions including data infrastructure, pipelines, etc. for collecting, storing ...

$104K - $125K/yr

As a Lead Data Engineer, you will serve as a senior individual contributor responsible for defining technical direction, leading complex Data Engineering initiatives, and building scalable, reliable ...

New

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 ...

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Data Engineer #1055558 * Employees in this job function are responsible for designing, building, and maintaining data solutions including data infrastructure, pipelines, etc. for collecting, storing ...

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 ...

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 ...

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Data Engineer #1054720 * Employees in this job function are responsible for designing, building, and maintaining data solutions including data infrastructure, pipelines, etc. for collecting, storing ...

Data Engineer

Lansing, MI · On-site

$116K - $139K/yr

Data Engineer Location: Lansing, MI (Need only locals, F2F is must) Rate: Market Duration: long term Required Skills: 12+ years developing complex database systems. 8+ years Databricks. 8+ years ...

$104K - $125K/yr

What is your role? As a Senior Data Engineer, you will design, build, optimize, and maintain scalable data pipelines, curated datasets, and cloud-based data solutions supporting Corning ...

New

$104K - $125K/yr

What is your role? As a Senior Data Engineer, you will design, build, optimize, and maintain scalable data pipelines, curated datasets, and cloud-based data solutions supporting Corning ...

New

Cloud Data Engineer

Ada, MI · On-site

$92K - $113K/yr

Cloud Data Engineer Posting Start Date: 5/18/26 Posting Location: Ada (Grand Rapids), MI Requisition ID: 42951 Job title: Data Engineer Department / Division: Data Engineering & Enterprise ...

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Role- Data Engineer Work location Dearborn, MI Ideal to be local but not required. 12 month contract. Additional Information: Resources will be in office 4 days a week. Teams Video interview 1 hour ...

Sr. Data Engineer

Grand Rapids, MI · On-site

$110K - $132K/yr

Overview The Sr. Data Engineer will serve as a key technical contributor responsible for the design, development, and ongoing support of the company's enterprise data platform and business ...

Palantir, Data Engineer

Detroit, MI · Remote

$113K - $135K/yr

A healthcare company based in the Midwest is looking to hire a remote Data Engineer with some monthly regional travel. They are midway through a Palantir Foundry implementation, and are looking for ...

Cloud Data Engineer

Ada, MI · On-site

$92K - $113K/yr

Data Engineer Department / Division: Data Engineering & Enterprise Integrations/ Data Warehousing Salary Range: $92,196/yr - $113,890/yr plus bonus Location: Ada, MI (onsite) What we're looking for:

Palantir, Data Engineer

Detroit, MI · Remote

$113K - $135K/yr

A healthcare company based in the Midwest is looking to hire a remote Data Engineer with some monthly regional travel. They are midway through a Palantir Foundry implementation, and are looking for ...

Data Engineer

Dearborn, MI

$105K - $126K/yr

Data Engineer #1059594 * As a Data Engineer on the Wrangling and Visualization Migration Team, you will communicate and collaborate with developers, architects, product managers, and feature teams to ...

next page

Showing results 1-20

Data Engineer information

See Michigan salary details

$38.8K

$113.1K

$154.7K

How much do data engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data engineer in Michigan is $113,060.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $119,800.00 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.
What are the most commonly searched types of Data Engineer jobs in Michigan? The most popular types of Data Engineer jobs in Michigan are:
What are popular job titles related to Data Engineer jobs in Michigan? For Data Engineer jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Data Engineer jobs? Cities in Michigan with the most Data Engineer job openings:
What are popular job titles related to Data Engineer jobs in MI? For Data Engineer jobs in MI, the most frequently searched job titles are:
Data Engineer

Data Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 10 days ago


Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 128 frontline employees who took The Breakroom Quiz

15th of 44 rated automakers


Job description

Job Summary:
Stellantis is looking for a Senior Data Engineer to join their AI & Data Analytics Team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that process massive datasets in both batch and real-time, ensuring scalable and reliable data architecture.
Responsibilities:
• Pipeline Development: Design and implement complex data processing pipelines using Apache Spark.
• Architectural Leadership: Build scalable, distributed systems that handle high-throughput data streams and large-scale batch processing.
• Infrastructure as Code: Manage and provision cloud infrastructure using Terraform.
• CI/CD & Automation: Streamline development workflows by implementing and maintaining GitHub Actions for automated testing and deployment.
• Code Quality: Uphold rigorous software engineering standards, including comprehensive unit/integration testing, code reviews, and maintainable documentation.
• Collaboration: Work closely with stakeholders to translate business requirements into technical specifications.
Qualifications:
Required:
• BA/BSc in Computer Science, Engineering, Mathematics, or a related technical discipline
• 5+ years of experience in the data engineering and software development life cycle.
• 4+ years of hands-on experience in building and maintaining production data applications, current experience in both relational and columnar data stores.
• 4+ years of hands-on experience working with AWS cloud services
• Comprehensive experience with one or more programming languages such as Python, Java, or Rust
• Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS S3, etc.)
• Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more
• Experience with workflow management engines (i.e., Airflow, Luigi, Azure Data Factory, etc.)
• Experience with designing and implementing real-time pipelines
• Experience with data quality and validation
• Experience with API design
• Distributed Computing: Deep expertise in Apache Spark (Core, SQL, and Structured Streaming).
• Programming Mastery: Strong proficiency in Scala or Java. You should be comfortable building production-grade applications in a JVM-based environment.
• SQL Proficiency: Advanced knowledge of SQL for data transformation, analysis, and performance tuning.
• DevOps & Tools: 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 design patterns. Experience applying 'Clean Code' principles to data engineering.
• Stream Processing: Experience with Apache Flink for low-latency stream processing.
• Scripting: Proficiency in Python for automation, data analysis, or scripting.
• Cloud Platforms: Experience with AWS, Azure, or GCP data services (e.g., EMR, Glue, Databricks).
• Data Modeling: Familiarity with dimensional modeling, Lakehouse architectures (Delta Lake, Iceberg), or NoSQL databases.
Preferred:
• Comprehensive knowledge of relational database concepts, including data architecture, operational data stores, Interface processes, multidimensional modeling, master data management, and data manipulation
• Expert knowledge and experience with custom ETL design, implementation and maintenance
• Comprehensive experience designing, implementing, and iterating data pipelines using Big Data technologies
• Certification in AWS or other cloud providers
• Experience with Databricks notebook workflows
• Experience with Terraform
Company:
Our storied and iconic brands embody the passion of their visionary founders and today’s customers in their innovative products and services: they include Abarth, Alfa Romeo, Chrysler, Citroën, Dodge, DS Automobiles, Fiat, Jeep®, Lancia, Maserati, Opel, Peugeot, Ram, Vauxhall and mobility brands Free2move and Leasys. Founded in 2007, the company is headquartered in Turin, ITA, with a team of 10001+ employees. The company is currently Late Stage.

What Stellantis employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom