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Databricks Engineer Jobs in Michigan (NOW HIRING)

Senior Data Engineer

Ann Arbor, MI · On-site

$103K - $140K/yr

Apply advanced technical knowledge to design, build, and optimize scalable data pipelines, reusable engineering frameworks, and platform capabilities using Azure Data Factory, Databricks, Spark ...

Senior Data Engineer

Ann Arbor, MI · On-site

$103K - $140K/yr

Apply advanced technical knowledge to design, build, and optimize scalable data pipelines, reusable engineering frameworks, and platform capabilities using Azure Data Factory, Databricks, Spark ...

$95K - $120K/yr

Experience with Databricks or comparable cloud-based data engineering platforms. * Experience ... developing and supporting Bronze, Silver, and Gold data layers or equivalent curated data models.

Senior Data Engineer

Ann Arbor, MI · On-site

$103K - $140K/yr

Apply advanced technical knowledge to design, build, and optimize scalable data pipelines, reusable engineering frameworks, and platform capabilities using Azure Data Factory, Databricks, Spark ...

At Corning, we are looking for an AI Engineer to help build, implement, and support AI-enabled ... and Databricks Genie Spaces use cases. - Partner with technical team members and business ...

Lead DevOps Engineer

Detroit, MI · On-site

$52.25 - $71.50/hr

... s Engineer Job Location: Detroit, MI Job Type: Contract * Collaborate with Agile development teams ... Databricks, networking, and container orchestration platforms in a repeatable and auditable manner.

At Corning, we are looking for an AI Engineer to help build, implement, and support AI-enabled ... and Databricks Genie Spaces use cases. - Partner with technical team members and business ...

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

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 ...

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

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:

$93K - $122K/yr

... Databricks or Databricks Genie Spaces. -Experience with model-serving endpoints or managed AI services. -Experience with prompt engineering, orchestration patterns, or AI workflow automation ...

Showing results 41-60

Databricks Engineer information

See Michigan salary details

$51.9K

$97.3K

$176.9K

How much do databricks engineer jobs pay per year?

As of Sep 5, 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 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?

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 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 $90,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, and data engineering can earn higher compensation, often including bonuses and benefits.

Is a Databricks engineer in demand?

Databricks engineers are in high demand due to the growing adoption of cloud-based data analytics and machine learning platforms. They typically require skills in Spark, SQL, and cloud environments like AWS or Azure, making them valuable in data-driven organizations across various industries.

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:

Infographic showing various Databricks Engineer job openings in Michigan as of August 2026, with employment types broken down into 85% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $97,298 per year, or $46.8 per hour.

Machine Learning Engineering

Publicis Groupe Holdings B.V

Birmingham, MI • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 12 days ago


Publicis Groupe rating

6.1

Company rating: 6.1 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

38th of 52 rated marketing agency


Job description

Company Description
Hi there! We're Razorfish. We've been leading the marketing industry with our digital expertise since the start of the internet. But in 2020, we did a full reboot. What's different? It all starts with people. Weird, wonderful, complex people - with diverse backgrounds in strategy, creative and technology. But no matter how different we are, we all have one thing in common. We believe our differences are our strength. So we push for inclusion, challenge convention and bring in new perspectives, to inspire new ideas. Because when we connect by understanding what makes people different, we can create unforgettable experiences that enrich lives. Join us at razorfish.com.
Overview
We're seeking a Machine Learning Engineer to help design, build, and maintain production-grade ML systems across cloud platforms. This role blends software engineering and ML expertise to translate prototypes into scalable solutions. You'll own the full ML lifecycle from development and deployment to monitoring and optimization using tools like Databricks, Vertex AI, and other cloud-native platforms. Strong technical skills, collaboration, and a passion for delivering AI at scale are essential.
For this role, we expect the candidate to demonstrate a track record of:
1. Collaborating with Data Science teams to deploy ML solutions into production.
2. Hands-on MLOps experience, including model deployment, monitoring, and lifecycle management.
3. Designing data warehouses and orchestrating data pipelines to support scalable ML operations.
Responsibilities
ML System Development & Deployment
  • Design, build, and maintain scalable ML pipelines using cloud services (e.g., Vertex AI, Databricks, SageMaker, Azure ML)
  • Develop and integrate microservices, REST APIs, and webhooks for ML model serving
  • Implement CI/CD pipelines for automated model training, testing, and deployment
  • Create robust data processing workflows for model training and inference

MLOps & Infrastructure
  • Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow, Vertex AI Pipelines)
  • Implement model monitoring, versioning, and performance tracking systems
  • Design automated retraining pipelines and manage model lifecycle
  • Ensure reliability, scalability, and security of models in production
  • Optimize inference performance and cost efficiency across cloud platforms

Software Engineering Excellence
  • Write clean, maintainable, and well-documented code following best practices
  • Implement comprehensive testing strategies including unit, integration, and model testing
  • Contribute to technical design reviews and architecture decisions
  • Maintain high code quality standards and participate in code reviews

Cross-Functional Collaboration
  • Partner with data scientists to productionize research models and prototypes
  • Collaborate with data engineers to design efficient data pipelines and feature stores
  • Work with product teams to integrate ML capabilities into customer-facing applications
  • Participate in agile development processes and cross-functional project planning
  • Provide technical guidance and mentorship to junior team members

Qualifications
Education & Experience
  • Bachelor's degree in Computer Science, Software Engineering, Data Science, Mathematics, or related field
  • 3-4 years of professional experience in ML engineering, software engineering, or data science
  • 2+ years of hands-on experience deploying and maintaining ML models in production
  • Experience working in collaborative, cross-functional team environments

Technical Skills
  • Programming Languages: Strong proficiency in Python and SQL (2+ years)
  • ML Frameworks: Experience with XGBoost, TensorFlow, PyTorch, sklearn, or Keras
  • Cloud Platforms: Solid hands-on experience with GCP, AWS, or Azure
  • ML Platforms: Practical knowledge of Vertex AI, SageMaker, Azure ML, or Databricks
  • Analytics & Feature Engineering: Proficient with BigQuery, Redshift, Azure Synapse
  • Distributed Processing: Skilled in Databricks, Apache Spark, Dataflow, Pub/Sub, Kafka
  • Workflow Orchestration: Experience with Airflow, Cloud Composer, Jenkins
  • Networking & Security: Understanding of cloud networking, security, and cost optimization
  • MLOps & DevOps: Familiarity with CI/CD, ML lifecycle management
  • API Development: Experience with REST APIs and microservices
  • Version Control: Proficiency with Git and collaborative development workflows

Core Competencies
  • Strong understanding of ML algorithms, model evaluation, and validation
  • Experience with data preprocessing, feature engineering, and performance tuning
  • Solid software engineering fundamentals and coding best practices
  • Awareness of data privacy, security, and ethical AI principles
  • Excellent collaboration skills with technical and non-technical stakeholders
  • Self-driven learner with curiosity about emerging ML technologies

Preferred Qualifications
Advanced Technical Skills
  • MLOps Tools: MLflow, Kubeflow, Vertex AI Pipelines
  • Containerization: Docker; basic Kubernetes knowledge
  • Specialized ML: Exposure to NLP, computer vision, or deep learning
  • Modern ML: Familiarity with LLMs, RAG patterns, transformer architectures

Professional Experience
  • Agile development and cross-functional collaboration
  • Code review and technical documentation practices
  • Interest in mentorship and knowledge sharing
  • Experience with model validation and software testing principles

Additional Information
The Power of One starts with our people! To do powerful things, we offer powerful resources. Our best-in-class wellness and benefits offerings include:
  • Paid Family Care for parents and caregivers for 12 weeks or more
  • Monetary assistance and support for Adoption, Surrogacy and Fertility
  • Monetary assistance and support for pet adoption
  • Employee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance
  • Tuition Assistance
  • Paid time off that includes Flexible Time off Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more
  • Matching Gifts programs
  • Flexible working arrangements
  • 'Work Your World' Program encouraging employees to work from anywhere Publicis Groupe has an office for up to 6 weeks a year (based upon eligibility)
  • Business Resource Groups that support multiple affinities and alliances

The benefits offerings listed are available to eligible U.S. Based employees, are reviewed on an annual basis, and are governed by the terms of the applicable plan documents.
Razorfish is an Equal Opportunity Employer. Our employment decisions are made without regard to actual or perceived race, color, ethnicity, religion, creed, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, childbirth and related medical conditions, national origin, ancestry, citizenship status, age, disability, medical condition as defined by applicable state law, genetic information, marital status, military service and veteran status, or any other characteristic protected by applicable federal, state or local laws and ordinances.
If you require accommodation or assistance with the application or onboarding process specifically, please contact USMSTACompliance@publicis.com.
All your information will be kept confidential according to EEO guidelines.
Compensation Range: $87,210 to $119,300. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 9/1/25.
Compensation Range: USD $87,210.00 - USD $119,300.00/Annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 11/15/2025.

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