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Data Transformation Jobs in Michigan (NOW HIRING)

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

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 ...

I2U Systems, Inc.

Senior Data Engineer

Lansing, MI · On-site

$107K - $146K/yr

Experience developing and optimizing SQL queries, data models, and data transformation processes. Excellent written and verbal communication skills with the ability to communicate technical ...

New

HTC Global Services

Data Engineer

Farmington Hills, MI · On-site

$112K - $135K/yr

Create and maintain data models using joins, transformations, and normalization to improve usability and performance. * Ensure data quality, consistency, and integrity across datasets. * Validate ...

Stellantis

Data Engineer - Supply Chain

Auburn Hills, MI · On-site

$108K - $130K/yr

Strong proficiency in Python and SQL for data transformation and pipeline development * Experience designing and maintaining production-grade data pipelines and analytical data models * Hands-on ...

HTC Global Services

Data Engineer

Farmington Hills, MI · On-site

$112K - $135K/yr

Create and maintain data models using joins, transformations, and normalization to improve usability and performance. * Ensure data quality, consistency, and integrity across datasets. * Validate ...

Global IT Family

Data Warehouse Architect

Lansing, MI · On-site

Use Python and XML to automate processes, perform data transformations, and integrate automation into ETL workflows. Work extensively in Linux/Unix environments to write shell scripts, manage file ...

Stellantis

Senior Data Engineer

Auburn Hills, MI

$100K - $136K/yr

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 ...

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All JobsData Transformation JobsData Transformation Jobs in Michigan

Data Transformation information

See Michigan salary details

$40.1K

$143.8K

$212.2K

How much do data transformation jobs pay per year?

As of Aug 6, 2026, the average yearly pay for data transformation in Michigan is $143,829.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,400.00 and $148,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the data transformation position, and why are they important?

To thrive in a Data Transformation role, a strong background in data analysis, data modeling, and database management is essential, often supported by a degree in computer science, information systems, or a related field. Proficiency with data transformation tools like SQL, ETL platforms (such as Informatica or Talend), and cloud data services is typically required, and certifications in these areas can be advantageous. Strong problem-solving skills, attention to detail, and effective communication abilities are key for collaborating with cross-functional teams and addressing complex data challenges. These skills and qualities are important because they ensure accurate, efficient data transformations that support critical business decisions.

What are the typical daily responsibilities of someone in a data transformation role?

In a Data Transformation role, your daily responsibilities often include analyzing raw data from multiple sources, designing and executing processes to clean and reformat data, and collaborating with business and IT teams to ensure data meets project requirements. You’ll typically work with ETL (Extract, Transform, Load) tools to automate and streamline these processes, as well as perform quality checks to validate data accuracy. Coordinating with data engineers, data analysts, and stakeholders is a key part of the job to ensure projects align with business goals. Staying up-to-date with new data management technologies and best practices can also be a regular part of your routine, helping to drive ongoing improvements.

What is a data transformation?

A Data Transformation job involves converting, structuring, and optimizing raw data to make it useful for analysis, reporting, or other business processes. Professionals in this role use ETL (Extract, Transform, Load) tools, coding languages like SQL or Python, and cloud platforms to clean, aggregate, and reformat data. They ensure data integrity, improve accessibility, and support data-driven decision-making. This role is essential in industries that rely on accurate and efficient data processing, such as finance, healthcare, and e-commerce.

What are popular job titles related to Data Transformation jobs in Michigan? For Data Transformation jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Data Transformation jobs in Michigan look for? The top searched job categories for Data Transformation jobs in Michigan are:
Data Transformation jobs near you
Infographic showing various Data Transformation job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $143,829 per year, or $69.1 per hour.

Data Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 4 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

14th of 44 rated automakers

Job description

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our 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. You will work at the intersection of software engineering and data science, ensuring that our data architecture is scalable, reliable, and follows industry best practices.
Priorities can change in a fast-paced environment like ours, so this role includes, but is not limited to, the following 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.

Basic Qualifications:
  • Bachelors degree in Computer Science, Engineering, Mathematics, or a related technical discipline
  • A minimum of 5 years of experience in the data engineering and software development life cycle. Including:
    • A minimum of 4 years of hands-on experience in building and maintaining production data applications, current experience in both relational and columnar data stores.
    • A minimum of 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 Qualifications:
  • 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

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