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Databricks Engineer Jobs in Michigan (NOW HIRING)

Stellantis

Ontology Engineer

Auburn Hills, MI · On-site

... Databricks, helping the team evolve toward advanced capabilities, including AI-enhanced insights ... data engineering position - not a dashboard/reporting development role. As Stellantis operates ...

Trilyon, Inc.

Sr. Data Engineer - Lansing, MI

Lansing, MI · On-site

$116K - $139K/yr

The ideal candidate will have strong experience in Databricks, AWS, Python/Scala, Oracle, and ... Job Title: Senior Data Engineer Location: Lansing, MI (Hybrid - Onsite 2 days/week, REQUIRED ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role ... Experience with Databricks notebook workflows * Experience with Terraform

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Stellantis is looking for a Senior Data Engineer to join their AI & Data Analytics Team. In this ... Experience with AWS, Azure, or GCP data services (e.g., EMR, Glue, Databricks). • Data Modeling:

Sun Communities, Inc.

Senior Data Engineer

Southfield, MI · On-site

$97K - $132K/yr

Configures, validates, and implements various Azure tools such as but not limited to Databricks ... Experience with one or more object-oriented programming languages such as Python, C#, Java or ...

Sun, Inc.

Senior Data Engineer

Southfield, MI · On-site

$97K - $132K/yr

Configures, validates, and implements various Azure tools such as but not limited to Databricks ... Experience with one or more object-oriented programming languages such as Python, C#, Java or ...

Apollo ITS

Data Engineer (Azure)

Grand Rapids, MI · On-site

$106K - $127K/yr

Data Engineer (Azure) Location: Grand Rapids, MI Duration: Long Term The ideal candidate for this ... Strong experience with Azure Data Factory (ADF), Databricks, and Synapse Analytics. * Required ...

Sun RV Resorts

Senior Data Engineer

Southfield, MI · On-site

$97K - $132K/yr

Configures, validates, and implements various Azure tools such as but not limited to Databricks ... Experience with one or more object-oriented programming languages such as Python, C#, Java or ...

Utilidata

Principal Data Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

We're looking for a Principal Data Engineer to own the technical direction and execution of our ... Background working with visualization tools connected to Databricks (Databricks Dashboards, Tableau ...

General Motors

Senior Software Engineer - Platform

Warren, MI · On-site

$115K - $151K/yr

Experience with Databricks Asset Bundles, GitHub Actions, or similar modern delivery tooling ... enabled engineering tools * Familiarity with MCP-style integrations and AI tools that connect to ...

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All JobsDatabricks Engineer JobsDatabricks Engineer Jobs in Michigan

Databricks Engineer information

See Michigan salary details

$51.9K

$97.3K

$176.9K

How much do databricks engineer jobs pay per year?

As of Jul 4, 2026, the average yearly pay for databricks engineer in Michigan is $97,298.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,200.00 and $115,500.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior Databricks Engineers with extensive experience, specialized skills in big data, cloud platforms, and advanced analytics can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or with significant bonuses and stock options. Such compensation typically requires a combination of technical expertise, leadership roles, and years of industry experience.

Is Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and the need for expertise in big data processing, Spark, and cloud environments. Companies seek professionals skilled in data pipeline development, ETL processes, and cloud tools like AWS or Azure, making this a strong job market for qualified candidates.

What are some common challenges faced by Databricks Engineers when working with large-scale data pipelines?

Databricks Engineers often encounter challenges related to optimizing the performance and reliability of large-scale data pipelines. These can include efficiently managing cluster resources, handling data partitioning to prevent bottlenecks, and troubleshooting job failures due to resource constraints or data quality issues. Collaboration with data scientists, analysts, and DevOps teams is essential to ensure seamless integration and deployment of production workflows. Staying current with evolving Databricks features and best practices also plays a key role in overcoming these challenges.

How much does a Databricks engineer make?

A Databricks engineer's salary typically ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, or data engineering may earn higher compensation. Salaries can also vary based on industry demand and certifications held.

Is Databricks a high paying job?

A Databricks Engineer typically earns a high salary due to the specialized skills required in cloud computing, big data processing, and Spark platform expertise. Compensation varies based on experience, location, and certifications, but it is generally above average for data engineering roles.

What is a Databricks Engineer?

A Databricks Engineer is a data engineering professional who specializes in using the Databricks platform to build, manage, and optimize data pipelines and analytics solutions. They work with big data technologies like Apache Spark, Delta Lake, and cloud services to process and analyze large datasets efficiently. Their role often involves developing ETL (extract, transform, load) workflows, setting up data lakes, and ensuring data quality and performance for business intelligence and machine learning applications.

What are the key skills and qualifications needed to thrive as a Databricks Engineer, and why are they important?

To thrive as a Databricks Engineer, you need strong expertise in big data processing, cloud platforms (like AWS or Azure), and proficiency with languages such as Python, SQL, and Scala, often supported by a degree in computer science or a related field. Familiarity with Apache Spark, Databricks Workspace, version control systems like Git, and relevant Databricks certifications are typically required. Strong analytical thinking, collaboration, and effective communication skills help you understand business needs and work seamlessly with data teams. These skills ensure efficient data pipeline development, scalable analytics solutions, and successful integration of Databricks into organizational workflows.
What are popular job titles related to Databricks Engineer jobs in Michigan? For Databricks Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Michigan look for? The top searched job categories for Databricks Engineer jobs in Michigan are:
What cities in Michigan are hiring for Databricks Engineer jobs? Cities in Michigan with the most Databricks Engineer job openings:
Databricks Engineer jobs near you
Infographic showing various Databricks Engineer job openings in Michigan as of June 2026, with employment types broken down into 40% Full Time, 20% Part Time, and 40% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $97,298 per year, or $46.8 per hour.
Ontology Engineer

Ontology Engineer

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 10 days ago

Stellantis rating

7.4

Company rating: 7.4 out of 10

Based on 126 frontline employees who took The Breakroom Quiz

17th of 44 rated automakers

Job description

The Global Purchasing Business Analytics Team at Stellantis is seeking a Ontology Engineer to build and maintain robust backend data solutions in support of global purchasing analytics. This role is focused on designing scalable data models and developing high-quality, production-grade code in SQL and Python to support our enterprise analytics architecture. You will work across platforms such as Snowflake, Palantir Foundry, Power BI, and potentially Databricks, helping the team evolve toward advanced capabilities, including AI-enhanced insights. While you'll collaborate closely with analysts and business stakeholders, this is a data engineering position - not a dashboard/reporting development role. As Stellantis operates globally with diverse and region-specific systems, you will often need to integrate fragmented data sources and iteratively develop solutions without complete documentation or available SMEs. Success in this role requires initiative, curiosity, and a self-starting mindset - someone who can function as a data entrepreneur: discovering and connecting data across domains to drive business value in a complex enterprise environment. You will work on a globally distributed team. Working hours must include at least 4 hours of overlap with Eastern Standard Time (EST) to ensure strong collaboration.
Key Responsibilities include but not limited to:
  • Develop, optimize, and maintain SQL / PySpark-based data models to support analytical applications in Global Purchasing
  • Partner with data analysts to understand analytical requirements and translate them into well-structured backend data solutions
  • Implement data validation, transformation, and automation logic to ensure high data quality
    Write clean, efficient, and maintainable code using SQL, Python/PySpark, and TypeScript (where applicable)
  • Explore and connect new or unfamiliar datasets in an iterative and self-directed manner, especially where formal documentation or SMEs are unavailable.
  • Collaborate with cross-functional teams to connect complex data into usable data models.
  • Contribute to the adoption of AI-driven tooling and workflows where applicable

Basic Qualifications:
  • Bachelor of Science degree in Business, Business Administration, Supply Chain Management, Finance, Marketing, Economics, International Business, Accounting, Entrepreneurship, Engineering, or equivalent; Other technical degrees with business background also considered
  • 8 + years of experience in data engineering or related experience
  • Strong SQL coding skills
  • Familiarity with modern data platforms (e.g., Snowflake, Palantir Foundry, Databricks, etc.)
  • Experience with data modeling concepts, star/snowflake schemas, and analytics-ready data design
  • Ability to write clean, maintainable code and troubleshoot performance issues in large datasets
  • Comfortable working in a backend engineering role, supporting front-end dashboards without directly building reports.
  • Solid understanding of data pipelines, ETL/ELT workflows, and version control (e.g., Git)Strong self-learning skills and ability to work independently in ambiguous, data-discovery-driven scenarios.

Preferred Qualifications:
  • Proficiency in Python
  • Experience with TypeScript, especially in the context of Palantir or similar platforms
  • Familiarity with Power BI, but focused on backend data support rather than report creation
  • Exposure to AI/ML workflows or interest in supporting such projects
  • Experience working in Agile and/or cross-functional teams

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