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Databricks Engineer Jobs in Minnesota (NOW HIRING)

Centstone

Database Engineer (Azure)

Minneapolis, MN · On-site

The ideal candidate will have strong expertise in Azure SQL, Azure Data Lake, Azure Databricks ... engineering, cloud migration, and enterprise data platform experience are encouraged to apply.

NxT Level

Principal AI / ML Engineer

Minneapolis, MN · On-site +1

Expertise in Databricks/Apache Spark for large-scale data processing in AI/ML applications ... Proficiency in programming languages such as R, Python, and Java, with a focus on data exploration ...

NxT Level

Principal AI / ML Engineer

Minneapolis, MN · On-site

Expertise in Databricks/Apache Spark for large-scale data processing in AI/ML applications ... Proficiency in programming languages such as R, Python, and Java, with a focus on data exploration ...

Saransh Inc

Sr Azure Data Engineer (12+ yrs)

Minneapolis, MN · On-site

$57.50 - $71.25/hr

Title: Azure Data Engineer Location: Minneapolis, MN (Onsite from Day 1) Job Type: Contract ... Azure Databricks Responsibilities: * Design and develop scalable architectures using Azure ...

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Databricks Engineer information

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$58.3K

$109.3K

$198.8K

How much do databricks engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for databricks engineer in Minnesota is $109,333.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,800.00 and $129,800.00 per year, depending on experience, location, and employer.

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 architecture can earn higher compensation, often exceeding $160,000 per year.

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.

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, and their roles are often available across various industries seeking data-driven solutions.
What are popular job titles related to Databricks Engineer jobs in Minnesota? For Databricks Engineer jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Minnesota look for? The top searched job categories for Databricks Engineer jobs in Minnesota are:
Databricks Engineer jobs near you
Infographic showing various Databricks Engineer job openings in Minnesota as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $109,333 per year, or $52.6 per hour.

Lead Databricks Engineer with Python (Need Only local to MN)

Sovereign Technologies

Eagan, MN • On-site

Other

Posted 17 days ago

Job description

Title: Senior / Lead Data Engineer

Location: Eagan, MN (Hybrid – 2 days/week onsite)
Duration: 3–6 Months Contract-to-Hire
Start Date: ASAP

Job Summary

We are seeking a Senior/Lead Data Engineer to modernize and own enterprise data pipelines by migrating legacy SAS-based workflows to Python/PySpark on Databricks. The engineer will partner with SMEs during the transition period and eventually take ownership of a critical healthcare analytics pipeline supporting HEDIS reporting.

Key Responsibilities
  • Migrate legacy SAS pipelines to Python/PySpark on Databricks.
  • Design, build, and maintain scalable ETL/ELT pipelines.
  • Develop distributed data processing solutions using Databricks.
  • Create and optimize complex SQL queries.
  • Schedule, automate, and monitor data pipelines.
  • Work with AWS services including S3, Lambda, Glue, and EC2.
  • Manage Databricks notebooks, workflows, and clusters.
  • Collaborate with business stakeholders and SMEs to transition pipeline ownership.
  • Follow Agile methodologies and Git-based development practices.
Required Skills
  • 8+ years of Data Engineering experience.
  • Strong Python programming and scripting skills.
  • Hands-on PySpark development.
  • Extensive Databricks experience (Notebooks, Workflows, Cluster Management).
  • Experience processing large datasets in distributed environments.
  • Strong SQL skills.
  • AWS experience with:
    • S3
    • Glue
    • Lambda
    • EC2
  • Experience building and automating ETL/ELT pipelines.
  • Git/version control experience.
  • Agile/Scrum experience.
Preferred Skills
  • Experience with SAS-to-Python migration.
  • AI/Automation experience.
  • Healthcare or HEDIS domain experience.
  • Lead/Principal Data Engineering experience.
Must-Have Skills
  • Python
  • PySpark
  • Databricks
  • SQL
  • AWS (S3, Glue, Lambda, EC2)
  • ETL/ELT Pipeline Development
  • Distributed Data Processing
  • Git
  • Agile/Scrum
Nice-to-Have Skills
  • SAS Modernization
  • AI/Generative AI
  • Healthcare/HEDIS
  • Airflow or other workflow orchestration tools
  • Leadership/Pipeline Ownership experience

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