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Databricks Engineer Jobs in Missouri (NOW HIRING)

Deloitte

Sr Databricks Data Engineer

Kansas City, MO · On-site

$111K - $134K/yr

As a Senior Consultant - Databricks Engineer in our AI & Data practice, you will design, build, and optimize cloud-based data engineering solutions that support large-scale transformation. You will ...

W. R. Berkley

Databricks Data Engineer

Wildwood, MO

$107K - $129K/yr

The Databricks Data Engineer will help design, build, deploy, and maintain scalable and production grade data pipelines in modern cloud environments, enabling analytics, AI, ML, and decision ...

Deloitte

Databricks Data Engineer

Kansas City, MO

$111K - $134K/yr

As a Databricks Data Engineer, you will support the design, build, and optimization of cloud-based data engineering solutions that enable large-scale transformation. You will work with business and ...

Perficient

Databricks Lead Data Engineer

Saint Louis, MO · On-site

$107K - $128K/yr

As a Databricks Lead Data Engineer, you are expected to lead the development team and have strong development and programming skills in Python, SQL, Pyspark, Databricks, Notebook Repositories ...

Koantek

Data Engineer - Multiple Positions

Chesterfield, MO · On-site

$113K - $136K/yr

As a Data Engineer at Koantek, you will leverage advanced data engineering techniques and analytics ... Guarantee that Databricks best practices are applied throughout all projects to maintain high ...

Koantek

Data Engineer - Multiple Positions

Chesterfield, MO · Remote

$113K - $136K/yr

As a Data Engineer at Koantek, you will leverage advanced data engineering techniques and analytics ... Guarantee that Databricks best practices are applied throughout all projects to maintain high ...

Stellar IT Group

BioTech Data Engineer

Saint Louis, MO · On-site

$111K - $133K/yr

Remote The Biotech Data Engineer focuses on designing, building, and maintaining scalable Azure Databricks-based data pipelines and architectures that enable analytics, AI/ML, and reporting across ...

Deloitte

Databricks Manager

Saint Louis, MO · On-site +1

These solutions are powered by engineering for business advantage, transforming mission-critical ... Experience with Databricks MLOps or infrastructure setup * Experience coordinating delivery teams ...

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$55.8K

$104.7K

$190.4K

How much do databricks engineer jobs pay per year?

As of Jun 11, 2026, the average yearly pay for databricks engineer in Missouri is $104,711.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,500.00 and $124,300.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior engineers in high-demand fields such as software engineering, data engineering, and specialized roles like Databricks Engineers can earn $500,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and leadership responsibilities. Compensation often includes base salary, bonuses, and stock options, particularly in large tech companies or startups with significant funding.

Is it hard to get hired at Databricks?

Getting hired as a Databricks Engineer can be competitive, as the role requires strong skills in big data technologies, cloud platforms, and programming languages like Python or Scala. Candidates often need relevant experience, certifications, and a solid understanding of data engineering concepts to succeed in the hiring process.

What is the salary of engineer in Databricks?

The salary of a Databricks Engineer 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 company size and industry demand.

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 career choice with good job prospects.

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.

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.
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What cities in Missouri are hiring for Databricks Engineer jobs? Cities in Missouri with the most Databricks Engineer job openings:
Databricks Engineer jobs near you
Infographic showing various Databricks Engineer job openings in Missouri as of June 2026, with employment types broken down into 99% Full Time, and 1% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $104,711 per year, or $50.3 per hour.

Databricks Engineer

Purple Drive Technologies

O Fallon, MO • On-site

Full-time

Posted 11 days ago

Job description

Overview:
Experience Required - 8+ Years
Must Have Technical/Functional Skills
• Tenured in the fields of Computer Science/Engineering or Software Engineering.
• Bachelor's degree in computer science, or a related technical field including programming with 15+ years of demonstrated experience in software development and delivery.
• Deep hands-on experience with Databricks and Python.
• Spark and SQL Expertise: Writing performant Spark SQL and PySpark transformations. Optimizing joins, window functions, and aggregations. Handling large-scale data with partitioning and caching strategies
• Experience with real-time data processing and streaming pipelines.
• Proficient in both Delta Live Tables (DLT) and Workflows - Understanding of Lakeflow Declarative Pipelines is an asset.
• DevOps and CI/CD - Using Databricks Asset Bundles (DABs) for deployment - Integrating with Git, Bitbucket, and Jenkins for version control and automation
• Proven track record using dbt for building robust, testable data transformation workflows following TDD.
• Strong grasp of cloud-based database infrastructure (AWS, Azure, or GCP).
• Skilled in developing insightful dashboards and scalable data models using Power BI.
• Expert in SQL development and performance optimization.
• Demonstrated success in building and maintaining data observability tools and frameworks.
• Proven ability to plan and execute deployments, upgrades, and migrations with minimal disruption to operations.

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