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Data Engineer Project Jobs in Michigan (NOW HIRING)

IntraEdge

AI Data Engineer

Detroit, MI

$113K - $136K/yr

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 ...

Deloitte

Data Engineer II

Grand Rapids, MI · On-site

$110K - $132K/yr

As an experienced Data Engineer , you will have the ability to share new ideas and collaborate on ... Project Talent Model (PTM) is a talent model that is tailored specifically for long-term, onsite ...

Howmet Aerospace

Data Engineer

Whitehall, MI · On-site

$108K - $130K/yr

Document projects in Power Point and reusable code, storing work in a revision-controlled system ... transform data with a programming language Strong working knowledge of Microsoft Office skills ...

Pwc

Data Engineer - Senior Manager

Detroit, MI · On-site

$124K - $280K/yr

As a Senior Manager you lead large projects, innovate processes, and maintain operational ... Data Engineer Associate] is a plus - Designing and implementing thorough data architecture ...

Deloitte

Data Engineer II

Lansing, MI · On-site

$116K - $139K/yr

As an experienced Data Engineer , you will have the ability to share new ideas and collaborate on ... Project Talent Model (PTM) is a talent model that is tailored specifically for long-term, onsite ...

Deloitte

Data Engineer II

Midland, MI · On-site

$98K - $118K/yr

As an experienced Data Engineer , you will have the ability to share new ideas and collaborate on ... Project Talent Model (PTM) is a talent model that is tailored specifically for long-term, onsite ...

Pwc

Data Engineer - Senior Manager

Grand Rapids, MI · On-site

$124K - $280K/yr

As a Senior Manager you lead large projects, innovate processes, and maintain operational ... Data Engineer Associate] is a plus - Designing and implementing thorough data architecture ...

Deloitte

Sr Databricks Data Engineer

Detroit, MI · On-site

$113K - $136K/yr

Lead, coach, and develop teams of data engineers and architects, fostering technical growth and effective project delivery. Data Governance: Consult on, design, and implement governance, security ...

Select Minds LLC

Big Data Engineer

Lansing, MI · On-site

$110K - $125K/yr

Opportunity for advancement Big Data Engineer Location: Chicago, IL (Day 1 Onsite) Hybrid Job Type ... Minimum of two end-to-end Big Data implementation projects. * Ability to work independently and ...

Select Minds LLC

Big Data Engineer

Lansing, MI · On-site

$110K - $125K/yr

Opportunity for advancement Big Data Engineer Location: Chicago, IL (Day 1 Onsite) Hybrid Job Type ... Minimum of two end-to-end Big Data implementation projects. * Ability to work independently and ...

Orbion Space Technology

Senior Data Engineer

Houghton, MI · On-site

$90K - $122K/yr

Mentor junior developers in software development projects * Perform other duties as assigned ... Experience with physical data and experimental methods * Experience in a manufacturing environment ...

ORBION SPACE TECHNOLOGY INC

Senior Data Engineer

Houghton, MI · On-site

$90K - $122K/yr

Description SENIOR DATA ENGINEER Orbion is seeking a Senior Data Engineer/Software Developer Orbion ... Mentor junior developers in software development projects * Perform other duties as assigned ...

Mariana Minerals

Sr. Data Engineer

Ann Arbor, MI · On-site

$103K - $140K/yr

They are seeking a Senior Data Engineer to design and build data pipelines that ensure the ... Mariana Minerals develops mineral projects using technology to supply critical minerals for energy ...

Cognizant Technologies

MI · On-site

$102K - $139K/yr

... and analytics projects Help drive a best-in-class data engineering practice that will be leveraged across GE Participates in setting strategy and standards through data architecture and ...

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Showing results 21-40

All JobsData Engineer Project JobsData Engineer Project Jobs in Michigan

Data Engineer Project information

What is a data engineer project?

A Data Engineer Project refers to a specific initiative or assignment undertaken by data engineers to design, build, and maintain systems that gather, process, and store large volumes of data. These projects often involve creating data pipelines, integrating multiple data sources, ensuring data quality, and optimizing storage solutions for analytics or business intelligence. Such projects are critical for organizations to manage their data efficiently and enable data-driven decision-making. Data Engineer Projects can range from building a data warehouse to implementing real-time data streaming solutions.

What are some common challenges faced by data engineers working on project-based teams?

Data Engineers on project-based teams often encounter challenges such as integrating data from disparate sources, ensuring data quality and consistency, and meeting tight project deadlines. Collaboration with data scientists, analysts, and software engineers is crucial, requiring clear communication to translate business needs into robust data pipelines. Additionally, adapting to evolving technologies and toolsets is essential for the successful delivery of scalable and maintainable solutions.

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 strong proficiency in programming (Python, Java, or Scala), data modeling, and database management, often supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), ETL systems, cloud platforms (AWS, Azure, GCP), and relevant certifications is highly beneficial. Analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating with data teams and stakeholders. These competencies are essential for building reliable data pipelines and ensuring data availability and quality to drive business insights.

What is the difference between Data Engineer Project vs Data Engineer?

AspectData Engineer ProjectData Engineer
CredentialsTypically requires a degree in Computer Science, Data Science, or related fields; certifications like AWS, Google Cloud, or Azure are commonSimilar credentials; often holds certifications in cloud platforms and data tools
Work EnvironmentProject-based, often temporary teams working on specific data solutionsFull-time role within organizations, maintaining ongoing data pipelines and infrastructure
Industry UsageUsed across industries for specific data initiativesCore role in data-driven companies and departments
Search & Comparison IntentOften searched for project-based roles or freelance opportunitiesMore common in job searches for permanent positions

In summary, Data Engineer Projects focus on temporary, goal-specific data tasks, while Data Engineers hold ongoing roles responsible for maintaining data infrastructure. Both roles require similar skills and certifications but differ mainly in scope and employment type.

Are data engineers still in high demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. Skills in cloud platforms, data pipeline development, and tools like SQL, Python, and Apache Spark enhance job prospects in this field.

Is a data engineer paid well?

Data engineers are generally well-compensated due to their specialized skills in managing large datasets, working with tools like SQL, Python, and cloud platforms. Salaries vary by experience, location, and industry, but they tend to be higher than average for tech roles, reflecting the demand for data infrastructure expertise.

What are popular job titles related to Data Engineer Project jobs in Michigan?

For Data Engineer Project jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Data Engineer Project jobs in Michigan look for?

The top searched job categories for Data Engineer Project jobs in Michigan are:

What cities in Michigan are hiring for Data Engineer Project jobs?

Cities in Michigan with the most Data Engineer Project job openings:

Data Engineer Project jobs near you
Infographic showing various Data Engineer Project job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 12% Part Time, 1% Temporary, and 5% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

AI Data Engineer

Detroit, MI

IntraEdge
IT Services • 1 - 5K employees
Learn more about IntraEdgeexternal

$113K - $136K/yr

Full-time

Re-posted 2 days ago

Key responsibilities

  • Design, construct, and optimize scalable AI and ML data pipelines, including ETL and ELT processes.

  • Develop and manage data architectures such as data lakes, data warehouses, and vector databases to support AI workloads.

  • Implement data validation, security, and governance policies to ensure data quality, integrity, and compliance.

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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