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Entry Level Ai Data Engineer Jobs in Michigan (NOW HIRING)

IntraEdge

AI Data Engineer

Detroit, MI

$113K - $136K/yr

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 ...

Deloitte

AI Engineer Consultant

Detroit, MI · Hybrid

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non ...

Corning

$104K - $125K/yr

... AI and machine learning? Join Corning's Optical Communications team and help transform complex ... As a Data Engineer, you will build, maintain, and support data pipelines and cloud-based data ...

Corning

$104K - $125K/yr

... AI/ML applications across a global organization. What is your role? As a Senior Data Engineer, you ... will design, build, optimize, and maintain scalable data pipelines, curated datasets, and cloud ...

IBM

Associate Data Engineer 2027 - AI & Analytics

Lansing, MI · On-site

$59K - $60K/yr

Work side-by-side with experienced consultants, data engineers, data scientists, AI specialists ... entry-level positions. You'll receive a status update email for each application, so be sure to ...

Stellantis

ICT Data Engineer

Auburn Hills, MI

$108K - $130K/yr

We are seeking a strategic and hands-on Data Engineer to support Purchasing and Finance Analytics and Programs within our North America Data & AI team. Data engineering is the practice of making the ...

Stellantis

ICT Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

We are seeking a strategic and hands-on Data Engineer to support Purchasing and Finance Analytics and Programs within our North America Data & AI team. Data engineering is the practice of making the ...

Hearst Newspapers

Full-Stack Data Engineer

Troy, MI · On-site

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

Hearst

Full-Stack Data Engineer

Troy, MI · On-site

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

Hearst

Full-Stack Data Engineer

Troy, MI · On-site

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

Hearst

Full-Stack Data Engineer

Troy, MI · On-site

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

Hearst

Full-Stack Data Engineer

Troy, MI

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

Hearst

Full-Stack Data Engineer

Troy, MI · On-site

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

Hearst

Full-Stack Data Engineer

Troy, MI · On-site

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

Hearst Newspapers

Full-Stack Data Engineer

Troy, MI

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

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All JobsAi Data Engineer JobsEntry Level Ai Data Engineer JobsEntry Level Ai Data Engineer Jobs in Michigan

Entry Level Ai Data Engineer information

What is an entry level AI data engineer?

An Entry Level AI Data Engineer is a professional who helps build and maintain data pipelines and infrastructure to support artificial intelligence and machine learning applications. They typically work with large volumes of data, ensuring it is properly collected, cleaned, and organized for analysis. Their responsibilities may include working with databases, data processing tools, and cloud platforms, as well as collaborating with data scientists and software engineers to enable AI-driven solutions. This role is ideal for recent graduates or those new to the field, providing foundational experience in data engineering within the context of AI.

What are some common challenges faced by entry level AI data engineers in their first year on the job?

Entry level AI data engineers often encounter challenges such as learning to manage large datasets efficiently, understanding complex data pipelines, and adapting to rapidly evolving AI tools and frameworks. Collaborating with data scientists and senior engineers can be initially overwhelming, but it's a great opportunity to learn industry best practices. Balancing multiple tasks like data cleaning, preprocessing, and supporting model deployment while honing programming skills is typical. Proactively seeking feedback and asking questions is key to overcoming these hurdles and growing in the role.

What are the key skills and qualifications needed to thrive as an entry level AI data engineer, and why are they important?

To thrive as an Entry Level AI Data Engineer, you need proficiency in programming languages like Python or Java, a foundational understanding of data structures and algorithms, and a relevant degree in computer science or a related field. Familiarity with data processing frameworks (e.g., Hadoop, Spark), cloud platforms (e.g., AWS, Azure), and basic knowledge of machine learning libraries are typically expected. Strong analytical thinking, attention to detail, and effective teamwork set outstanding candidates apart. These skills and qualities are crucial for building reliable data pipelines, supporting AI models, and ensuring efficient collaboration within technical teams.

What is the difference between Entry Level Ai Data Engineer vs Data Analyst?

AspectEntry Level Ai Data EngineerData Analyst
Required SkillsBasic programming, data modeling, understanding of AI/ML conceptsData visualization, statistical analysis, SQL proficiency
CertificationsPython, SQL, entry-level AI/ML coursesExcel, Tableau, SQL certifications
Work EnvironmentTech companies, AI startups, data-driven teamsBusiness, marketing, finance sectors
Job FocusBuilding AI models, data pipelines, integrating AI solutionsInterpreting data, creating reports, supporting decision-making

While both roles involve working with data, Entry Level Ai Data Engineers focus on developing AI models and data infrastructure, whereas Data Analysts primarily analyze data to generate insights. The former requires some knowledge of AI/ML, while the latter emphasizes statistical and visualization skills.

How to get into entry level AI data engineering?

To enter an entry-level AI data engineering role, develop skills in programming languages like Python and SQL, understand data pipelines and databases, and gain experience with cloud platforms such as AWS or Azure. Completing relevant certifications or courses in data engineering and machine learning can also improve job prospects.

What are popular job titles related to Entry Level Ai Data Engineer jobs in Michigan?

For Entry Level Ai Data Engineer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Entry Level Ai Data Engineer jobs in Michigan look for?

The top searched job categories for Entry Level Ai Data Engineer jobs in Michigan are:

What cities in Michigan are hiring for Entry Level Ai Data Engineer jobs?

Cities in Michigan with the most Entry Level Ai Data Engineer job openings:

Entry Level Ai Data Engineer jobs near you
Infographic showing various Entry Level Ai Data Engineer job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

AI Data Engineer

IntraEdge

Detroit, MI

$113K - $136K/yr

Full-time

Re-posted 28 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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