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Graduate Data Engineer Jobs in Michigan (NOW HIRING)

The Graduate Assistant - Athletic Administration at Aquinas College plays a critical support role ... programming. โ— Develop and refine skills in project management, data organization, and ...

Our global network is made up of architects, designers, planners, engineers, and environmental ... Data Collection and Analysis: Produce accurate reports for others by collecting data from a variety ...

Our global network is made up of architects, designers, planners, engineers, and environmental ... Data Collection and Analysis: Produce accurate reports for others by collecting data from a variety ...

Our global network is made up of architects, designers, planners, engineers, and environmental ... Data Collection and Analysis: Produce accurate reports for others by collecting data from a variety ...

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Graduate Data Engineer information

See Michigan salary details

$38.8K

$113.1K

$154.7K

How much do graduate data engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for graduate 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.

What are the key skills and qualifications needed to thrive in the Graduate Data Engineer position, and why are they important?

A Graduate Data Engineer typically requires a bachelor's degree in computer science, engineering, mathematics, or a related field, along with foundational knowledge of programming, data structures, and database concepts. Familiarity with technologies such as SQL, Python, cloud platforms (e.g., AWS, Azure), and modern data engineering tools like Apache Spark or Hadoop is often expected, and introductory certifications can provide an added advantage. Strong analytical thinking, problem-solving ability, effective communication, and eagerness to learn are valuable soft skills in this role. These skills and qualities are crucial for efficiently building, maintaining, and optimizing data pipelines that support business decision-making.

What are the typical daily tasks and responsibilities of a Graduate Data Engineer?

As a Graduate Data Engineer, your daily tasks may include building and maintaining data pipelines, assisting with data cleansing and transformation, and collaborating with data scientists and other engineers to deliver reliable datasets. You'll often work with structured and unstructured data, write scripts to automate data workflows, and help troubleshoot data integration issues as they arise. Throughout your work, you'll be expected to document processes and learn new tools or technologies as the team evolves. This role provides an excellent opportunity to develop hands-on technical skills while working closely with experienced professionals in a collaborative setting.

What is a Graduate Data Engineer job?

A Graduate Data Engineer is an entry-level role focused on designing, building, and maintaining data pipelines and infrastructure. They work with large datasets, ensuring data is collected, processed, and stored efficiently for analysis. Typically, they collaborate with data scientists, analysts, and other engineers to support data-driven decision-making. This role often involves using programming languages like Python or SQL, cloud platforms, and big data technologies. Graduate Data Engineers gain hands-on experience in data engineering principles and tools, helping organizations manage and optimize their data workflows.

Infographic showing various Graduate Data Engineer job openings in Michigan as of May 2026, with employment types broken down into 1% As Needed, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $113,060 per year, or $54.4 per hour.
Data Engineer (Python)

Data Engineer (Python)

Noblesoft Technologies

Auburn Hills, MI โ€ข On-site

$108K - $130K/yr

Contractor

Posted 6 days ago


Job description

Job Role: Senior Data Engineer (Python)

Location: Auburn Hills, MI
ย 

Mandatory Skills: Data Engineering, Python, PySpark, CI/CD, Airflow, Workflow Orchestration

Overall Experience: 8+ years of relevant experience

JOB REQUIREMENTS -

The Senior Data Engineer & Technical Lead (SDET Lead) will play a pivotal role in delivering major data engineering initiatives within the Data & Advanced Analytics space. This position requires hands-on expertise in building, deploying, and maintaining robust data pipelines using Python, PySpark, and Airflow, as well as designing and implementing CI/CD processes for data engineering projects

Key Responsibilities
1. Data Engineering: Design, develop, and optimize scalable data pipelines using Python and PySpark for batch and streaming workloads.
2. Workflow Orchestration: Build, schedule, and monitor complex workflows using Airflow, ensuring reliability and maintainability.
3. CI/CD Pipeline Development: Architect and implement CI/CD pipelines for data engineering projects using GitHub, Docker, and cloud-native solutions.
4. Testing & Quality: Apply test-driven development (TDD) practices and automate unit/integration tests for data pipelines.
5. Secure Development: Implement secure coding best practices and design patterns throughout the development lifecycle.
6. Collaboration: Work closely with Data Architects, QA teams, and business stakeholders to translate requirements into technical solutions.
7. Documentation: Create and maintain technical documentation, including process/data flow diagrams and system design artifacts.
8. Mentorship: Lead and mentor junior engineers, providing guidance on coding, testing, and deployment best practices.
9. Troubleshooting: Analyze and resolve technical issues across the data stack, including pipeline failures and performance bottlenecks.
Cross-Team Knowledge Sharing: Cross-train team members outside the project team (e.g., operations support) for full knowledge coverage.

Includes all above skills, plus the following;
ยทย ย ย ย ย ย ย ย  Minimum of 7+ years overall IT experience
ยทย ย ย ย ย ย ย ย  Experienced in waterfall, iterative, and agile methodologies

Technical Experience:

1. Hands-on Data Engineering : Minimum 5+ years of practical experience building production-grade data pipelines using Python and PySpark.
2. Airflow Expertise: Proven track record of designing, deploying, and managing Airflow DAGs in enterprise environments.
3. CI/CD for Data Projects : Ability to build and maintain CI/CD pipelines for data engineering workflows, including automated testing and deployment**.
4. Cloud & Containers: Experience with containerization (Docker and cloud platforms (GCP) for data engineering workloads. Appreciation for twelve-factor design principles
5. Python Fluency : Ability to write object-oriented Python code manage dependencies, and follow industry best practices
6. Version Control: Proficiency with **Git** for source code management and collaboration (commits, branching, merging, GitHub/GitLab workflows).
7. Unix/Linux: Strong command-line skills** in Unix-like environments.
8. SQL : Solid understanding of SQL for data ingestion and analysis.
9. Collaborative Development : Comfortable with code reviews, pair programming and using remote collaboration tools effectively.
10. Engineering Mindset: Writes code with an eye for maintainability and testability; excited to build production-grade software
11. Education: Bachelorโ€™s or graduate degree in Computer Science, Data Analytics or related field, or equivalent work experience.

Unique Skills

โ€ข Graduate degree in a related field, such as Computer Science or Data Analytics
โ€ข Familiarity with Test-Driven Development (TDD)
โ€ข A high tolerance for OpenShift, Cloudera, Tableau, Confluence, Jira, and other enterprise tools