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Data Engineer Jobs in Michigan (NOW HIRING)

IntraEdge

AI Data Engineer

Detroit, MI · On-site

$113K - $136K/yr

This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. Key responsibilities * Build AI-ready data pipelines: Design ...

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 ...

PROLIM Global Corporation

Data Engineer

Lansing, MI · On-site

$116K - $139K/yr

PROLIM (www.prolim.com) is currently seeking Data Engineer for one of our top Client for Location: Lansing, MI Qualified candidates can directly send your updated resume and contact info via email ...

New

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 ...

Bespoke Labs

Data Engineer

Detroit, MI · On-site

$113K - $135K/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 ...

Bespoke Labs

Data Engineer

Flint, MI · On-site

$111K - $133K/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 ...

Saanvi Technologies

Data Engineer 3

Dearborn, MI · On-site

$105K - $126K/yr

Data Engineer Dearborn, MI Hybrid 4days onsite and 1 day remote W2 Position Description: Ford Motor Company is seeking a Senior Technical Engineer to serve as a subject matter expert for the ATLAS ...

Bespoke Labs

Data Engineer

Lansing, MI · On-site

$116K - $139K/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 ...

Bespoke Labs

Data Engineer

Kalamazoo, MI · On-site

$108K - $130K/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 ...

Amway

Cloud Data Engineer

Ada, MI · On-site

$112K - $134K/yr

Amway is seeking an experienced Cloud Data Engineer to support the modernization of their enterprise data platform as they migrate to a cloud-native architecture on Google Cloud Platform (GCP). The ...

Bespoke Labs

Data Engineer

Mount Pleasant, 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 ...

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 ...

Bespoke Labs

Data Engineer

Ann Arbor, MI · On-site

$112K - $134K/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 ...

Bespoke Labs

Data Engineer

Berrien Springs, MI · On-site

$105K - $127K/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 ...

Bespoke Labs

Data Engineer

Allendale, MI · On-site

$99K - $119K/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 ...

Bespoke Labs

Data Engineer

Grand Rapids, MI · On-site

$110K - $132K/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 ...

Bespoke Labs

Data Engineer

Warren, MI · On-site

$107K - $129K/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 ...

3Core Systems, Inc.

Sr. Data Engineer

East Lansing, MI · On-site

$110K - $132K/yr

Job Title: Sr. Data Engineer - MS Fabric, ETL/ELT, Data Modelling, and Cloud platforms Location: Lansing, MI (Onsite-Hybrid) Duration: Long term contract Mode of Interview: In-Person interview Only ...

Bespoke Labs

Data Engineer

Sterling Heights, MI · On-site

$107K - $128K/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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Showing results 1-20

All JobsData Engineer JobsData Engineer Jobs in Michigan

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.
More about Data Engineer jobs
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 job categories do people searching Data Engineer jobs in Michigan look for? The top searched job categories for Data Engineer jobs in Michigan 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 jobs near you
AI Data Engineer

AI Data Engineer

IntraEdge

Detroit, MI • On-site

$113K - $136K/yr

Full-time

Posted 3 days ago

Job description

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued.

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued. 
Education:Employment Type: FULL_TIME
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About IntraEdge

Sourced by ZipRecruiter

At heart, we are a technology, products and services organization In our soul, it’s the people who make us what we are — the professionals we train and connect to next-level opportunities and the experts who create innovative solutions and value for our national and international partners. It’s true that innovative technology can provide a major boost to your business, but you also need the right talent pushing it forward. This critical combination is what we offer all of our partners: cutting edge tech solutions and the expertise to bring it to life.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chandler, AZ, US

Year founded

2002

Social media

Instagram

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