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Python Data Jobs in Michigan (NOW HIRING)

General Motors

Data Engineer

Warren, MI · On-site

$107K - $129K/yr

Develop and support end-to-end ETL/ELT workflows using Databricks notebooks, Python, Spark, and SQL ... Define and implement data transformations, semantic structures, and curated data assets that ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Develop and support data pipelines and ETL workflows using Python and SQL * Work with Databricks or similar data platforms for data processing and analytics * Implement DevSecOps practices, including ...

Delta Dental of Michigan

Data Scientist

Okemos, MI · On-site

To implement quantitative and predictive models, data science experiments using literate programming techniques such as Python Jupyter Notebooks, develop appropriate visualizations of data, curate ...

Delta Dental of Michigan

Data Scientist

Okemos, MI · Hybrid

To implement quantitative and predictive models, data science experiments using literate programming techniques such as Python Jupyter Notebooks, develop appropriate visualizations of data, curate ...

Tech Tammina LLC

Data Engineer

Lansing, MI · On-site

$116K - $139K/yr

Data Engineer Location: Lansing, MI (Need only locals, F2F is must) Rate: Market Duration ... Python/Scala. 8+ years Oracle. 5+ years' experience with Extract, Transform, and Load (ETL) ...

Epitec

Data Engineer

Southfield, MI · On-site

$114K/yr

Data Engineer (Job Code: 1391) Duties : Responsible for supporting vehicle feature level ... Python, GCP, Hadoop, Azure, Tableau, Alteryx, AWS, C++, Git, Embedded C, SQL, and Docker. Will also ...

Pwc

GenAI Python Systems Engineer-Manager

Detroit, MI

$99K - $232K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... Python and SQL - Experience with Docker and containerized deployments - Skilled in AI techniques ...

Agile Tech Labs

Data Scientist

Detroit, MI · On-site

Proficiency in Python. * Experience with cloud platforms (AWS preferred) and Big Data technologies. * Experience with Databricks is a plus. * Strong software development and coding best practices.

OpTech

Snowflake Data Analyst

Detroit, MI · On-site

$45 - $55/hr

Experience with Python, R, or other analytical tools. * Understanding of data warehousing and dimensional modeling concepts. * Experience working in cloud environments (AWS, Azure, or Google Cloud ...

Birdi

Principal Data Engineer

Plymouth, MI · Remote

$109K - $130K/yr

Tableau, Tableau Server, SSIS, SQL Server, PostgreSQL, Python, SSRS, Azure, Cloud, Git, CI/CD, Terraform, CloudFormation, HL7, FHIR Requirements: Senior data engineer with expertise in SQL Server ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

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 ...

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All JobsPython Data JobsPython Data Jobs in Michigan

Python Data information

See Michigan salary details

$11

$51

$75

How much do python data jobs pay per hour?

As of Jul 10, 2026, the average hourly pay for python data in Michigan is $51.09, according to ZipRecruiter salary data. Most workers in this role earn between $42.12 and $58.03 per hour, depending on experience, location, and employer.

What is the salary for Python data analytics?

The salary for Python data analysts typically ranges from $60,000 to $100,000 annually, depending on experience, location, and industry. Professionals with strong skills in data manipulation, visualization, and tools like Pandas and SQL tend to earn higher salaries.

What Python jobs are in demand?

Python data-related jobs in demand include data analyst, data scientist, machine learning engineer, and backend developer. These roles often require proficiency in libraries like Pandas, NumPy, and frameworks such as TensorFlow, with employers seeking strong programming skills and experience with data analysis or AI projects.

What are some common challenges faced by Python Data professionals when working with large datasets?

Python Data professionals often encounter challenges such as optimizing code to handle large volumes of data efficiently and managing memory usage to prevent slowdowns or crashes. Working with big datasets may require leveraging tools like pandas, NumPy, or Dask, and sometimes integrating with distributed computing systems such as Apache Spark. Additionally, ensuring data quality and managing data pipelines for consistent and accurate results can be demanding. Collaborating closely with data engineers, analysts, and other stakeholders is common to ensure smooth data flow and analysis.

What is a Python Data professional?

A Python Data professional is someone who uses the Python programming language to analyze, process, and interpret data. They work with large datasets, perform data cleaning and transformation, and apply statistical or machine learning techniques to extract insights. These professionals often work in roles such as data analyst, data scientist, or data engineer, and use Python libraries like Pandas, NumPy, and scikit-learn to accomplish their tasks.

Will AI replace Python devs?

Python developers are unlikely to be fully replaced by AI, as their role involves designing, coding, and maintaining complex software systems that require human judgment and creativity. AI tools can assist with tasks like code generation and debugging, but human oversight remains essential for quality and innovation. Staying updated with new frameworks and machine learning techniques can help Python developers remain valuable in the evolving tech landscape.

What is the difference between Python Data vs Data Analyst?

AspectPython DataData Analyst
Required SkillsPython programming, data manipulation, scriptingExcel, SQL, data visualization
CertificationsPython certifications, data science coursesData analysis certifications, Excel certifications
Work EnvironmentData science teams, programming-heavy rolesBusiness intelligence, reporting teams
Industry UsageTech, finance, healthcareRetail, marketing, finance

Python Data roles focus on programming, data manipulation, and building data pipelines using Python, while Data Analysts primarily analyze data using tools like Excel and SQL to generate reports and insights. Both roles often collaborate but differ in technical depth and tools used.

What type of jobs can I get with Python?

Python is used in a variety of roles including software developer, data analyst, data scientist, machine learning engineer, and automation engineer. These jobs often require knowledge of libraries like Pandas, NumPy, and frameworks such as TensorFlow or Django, and may involve working in environments like cloud platforms or data centers.

What are the key skills and qualifications needed to thrive as a Python Data professional, and why are they important?

To thrive as a Python Data professional, you need strong programming skills in Python, a solid understanding of data structures, algorithms, and experience with data analysis or data science, typically supported by a relevant degree. Familiarity with technical tools such as pandas, NumPy, SQL, Jupyter Notebooks, and often cloud platforms or machine learning frameworks is important, and certifications like Microsoft or Google Data certifications can be advantageous. Strong analytical thinking, attention to detail, and effective communication help you extract insights from data and collaborate with stakeholders. These skills and qualities are essential to efficiently process, analyze, and interpret data, driving informed business decisions.
What are popular job titles related to Python Data jobs in Michigan? For Python Data jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Python Data jobs in Michigan look for? The top searched job categories for Python Data jobs in Michigan are:
Python Data jobs near you
Infographic showing various Python Data job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $106,276 per year, or $51.1 per hour.
Data Engineer

Data Engineer

General Motors

Warren, MI • On-site

$107K - $129K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 2 days ago. Applications are no longer accepted.

General Motors rating

8.0

Company rating: 8.0 out of 10

Based on 308 frontline employees who took The Breakroom Quiz

6th of 44 rated automakers

Job description

Job Description
This role is categorized as hybrid. This means the successful candidate is expected to report to Warren Global Technical Center, Mountain View Technical Center, or Austin Technical Center three times per week, at minimum [or other frequency dictated by the business if more than 3 days].
The Role
This role will focus on designing, developing, and supporting Databricks-based pipelines, medallion-layer data products, and enterprise integrations that enable analytics, reporting, and AI use cases. The role also includes building and supporting data movement patterns both into Databricks and between enterprise applications, including solutions that leverage DataStage and related integration technologies.
You will partner closely with product owners, architects, data engineers, report and analytics teams, and source-system teams to define trusted data products, improve data quality and reliability, and deliver scalable solutions that support operational and executive decision-making.
What You'll Do
  • Design, build, and maintain scalable data pipelines in Databricks to ingest, transform, validate, and publish trusted data products for analytics, reporting, and AI use cases.
  • Develop and support end-to-end ETL/ELT workflows using Databricks notebooks, Python, Spark, and SQL, including orchestration, parameterization, error handling, restartability, and performance optimization.
  • Build and maintain Bronze, Silver, and Gold data products that are reusable, governed, and aligned to business and downstream consumption needs.
  • Build and support integrations both into Databricks and between enterprise applications, including legacy and modern integration patterns such as DataStage-based workflows.
  • Implement pipeline logic for ingestion, standardization, cleansing, enrichment, joins, aggregations, and publishing of curated data assets for downstream use.
  • Partner with product owners, architects, source-system teams, report and analytics teams, and data consumers to translate business needs into well-defined technical solutions and trusted data products.
  • Define and implement data transformations, semantic structures, and curated data assets that improve usability, consistency, downstream performance, and trust in the data.
  • Apply strong data quality, validation, reconciliation, and documentation practices to ensure data products are accurate, discoverable, reliable, and production-ready.
  • Use GitHub-based development practices for version control, code review, collaboration, and promotion of pipeline changes across environments.
  • Support secure and compliant data delivery by implementing access controls, permissions, and governance requirements in alignment with GM policies.
  • Monitor, troubleshoot, and improve pipeline health, runtime performance, cost efficiency, and operational stability across production data assets and integrations.
  • Help modernize legacy integrations and reporting patterns by standardizing and migrating solutions onto the enterprise data platform.
  • Contribute to team standards, reusable patterns, and best practices for notebooks, Python development, GitHub workflows, data engineering, integration design, data quality, and operational support.

Your Skills & Abilities (Required Qualifications)
  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, Data Science, Engineering, or a related field; or equivalent experience.
  • 5+ years of experience as a data engineer, ETL developer, or integration engineer building production-grade data pipelines and data products.
  • Hands-on experience with Databricks for data engineering and analytics enablement, including:
    • Strong SQL skills in Databricks
    • Experience building and supporting ETL/ELT pipelines in Databricks
    • Experience developing pipelines using Python, notebooks, DataStage, and scalable data transformation patterns
    • Experience with workflow orchestration, dependency management, scheduling, monitoring, and operational support of production pipelines.
  • Proven experience designing and implementing dimensional, layered, or medallion-style data models for analytics and operational use cases.
  • Strong knowledge of data warehousing and ETL/ELT concepts, including how upstream design impacts downstream performance, usability, and trust in data products.
  • Experience integrating data from enterprise applications, especially operational platforms such as ServiceNow.
  • Familiarity with DataStage and application-to-application integration patterns.
  • Experience using GitHub for source control, branching, pull requests, collaboration, and release management of data engineering assets.
  • Demonstrated ability to implement data quality, metadata, documentation, and governance practices in production data environments.
  • Strong collaboration skills and a track record of working effectively in cross-functional teams (data engineers, architects, product owners, business partners, and report and analytics teams).
  • Strong problem-solving, communication, and ownership skills, with the ability to operate effectively in a fast-moving environment.

What Can Give You a Competitive Advantage (Preferred Qualifications)
  • Experience supporting analytics, dashboards, or executive reporting use cases.
  • Experience working with ServiceNow data, including ITSM, CMDB, HRSD, or related operational domains.
  • Experience with secure data delivery, access controls, and enterprise governance standards.
  • Experience with production support, observability, and operational reporting for data platforms.
  • Familiarity with data dictionaries, lineage, and data product documentation or publishing practices.
  • Familiarity with cloud data platform patterns, particularly Databricks Lakehouse environments.
  • Experience working in Agile or product-centric environments with iterative delivery and continuous feedback.

This job may be eligible for relocation benefits.
Compensation:
  • The expected base compensation for this role is: $138,700 - $206,950. Actual base compensation within the identified range will vary based on factors relevant to the position.
  • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
  • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE. THIS INCLUDES DIRECT COMPANY SPONSORSHIP, ENTRY OF GM AS THE IMMIGRATION EMPLOYER OF RECORD ON A GOVERNMENT FORM, AND ANY WORK AUTHORIZATION REQUIRING A WRITTEN SUBMISSION OR OTHER IMMIGRATION SUPPORT FROM THE COMPANY (e.g., H-1B, OPT, STEM OPT, CPT, TN, J-1, etc.)
#LI-CC1
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.
Non-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
Accommodations
General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, emailus or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

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About General Motors

Sourced by ZipRecruiter

General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908

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