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Databricks Engineer Jobs in Missouri (NOW HIRING)

Koantek

Senior AI Engineer

Chesterfield, MO · Remote

$54.75 - $70.50/hr

Sr AI Engineer / Data Scientist / MLOps Consultant Location: United States - Remote Employment Type ... Preferred Qualifications Hands-on experience with modern ML platform stacks, such as Databricks ...

Pwc

Data Engineer - Senior Associate

Saint Louis, MO · On-site

$77K - $202K/yr

... Engineer - Senior Associate, you will focus on designing and building data infrastructure and ... Databricks Unified Data Analytics Platform for advanced data analytics and visualization ...

Pwc

Data Engineer - Senior Associate

Kansas City, MO · On-site

$77K - $202K/yr

... Engineer - Senior Associate, you will focus on designing and building data infrastructure and ... Databricks Unified Data Analytics Platform for advanced data analytics and visualization ...

Pwc

Data Engineer - Manager

Saint Louis, MO · On-site

$99K - $232K/yr

... Data Engineer - Manager, you will play a pivotal role in transforming raw data into actionable ... Databricks and Snowflake - Guiding team members in data architecture development and database ...

MasterCard

Senior Principal, Data Engineering

O Fallon, MO · On-site

$117K - $161K/yr

Mastercard Services Technology is seeking a Senior Principal Data Engineer to help drive our ... Databricks and related ecosystem tools. Lead by doing through hands-on development of DevOps ...

Pwc

Data Engineer - Manager

Kansas City, MO

$99K - $232K/yr

... Data Engineer - Manager, you will play a pivotal role in transforming raw data into actionable ... Databricks and Snowflake - Guiding team members in data architecture development and database ...

iQuasar LLC

Azure Cloud Engineer

Saint Louis, MO · On-site

$54 - $72.25/hr

... with Databricks or Spark * 1+ year working with technologies such as CosmoDB, AzureSQL, Redis, Synapse * 1+ year working with orchestration tool such as Airflow or Oozie * Strong programming ...

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All JobsDatabricks Engineer JobsDatabricks Engineer Jobs in Missouri

Databricks Engineer information

See Missouri salary details

$55.8K

$104.7K

$190.4K

How much do databricks engineer jobs pay per year?

As of Jul 13, 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 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 Missouri? For Databricks Engineer jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Missouri look for? The top searched job categories for Databricks Engineer jobs in Missouri are:
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
Senior AI Engineer

Senior AI Engineer

Koantek

Chesterfield, MO • Remote

$54.75 - $70.50/hr

Contractor

Re-posted 8 days ago

Job description

Sr AI Engineer / Data Scientist / MLOps Consultant Location: United States - Remote Employment Type: Full-Time and Contract We are seeking an experienced and highly technical Data Scientist to join our customer-facing consulting team. This remote role requires a blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation. The successful candidate will be instrumental in designing, deploying, and maintaining production-grade ML solutions, including advanced Generative AI and Natural Language Processing (NLP) models, for our diverse client base.Key Responsibilities Serve as a primary technical consultant, leading and executing end-to-end ML project implementations directly with clients, translating complex business problems into robust technical solutions

Exhibit excellent communication, presentation, and stakeholder management skills to clearly articulate technical findings, proposals, and project status to both technical and non-technical audiences. Design, build, and maintain production-grade ML pipelines, focusing on continuous integration, continuous delivery (CI/CD), and advanced MLOps practices to ensure reliability and scalability of models. Implement and optimize cutting-edge Generative AI and NLP applications, demonstrating hands-on experience with technologies like Retrieval Augmented Generation (RAG) and Large Language Models (LLMs) in a production setting.

Manage underlying solution infrastructure, demonstrating proficiency in technologies such as Docker, pipeline orchestrators, and database systems. Leverage expertise in distributed computing frameworks, specifically in scalable machine learning and high-performance data processing (e.g., using technologies like Apache Spark). Contribute to the strategic growth of the ML Practice Team, including participation in technical assignments and knowledge transfer activities

Ensure all client engagements and training activities are properly documented and reported via designated partner platforms. Required Qualifications 4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining models in a live environment. 3+ years of experience in a customer-facing consulting or solutions architect role, focused on technical implementation and delivery.

Excellent verbal and written communication skills for effective client and internal team interaction. Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated deployment best practices. Demonstrable experience with infrastructure management, encompassing containerization (Docker) and data pipeline orchestration.

Deep understanding of programming for data-intensive and scalable ML applications. Proven experience in deploying and managing Generative AI and NLP solutions for client applications. Preferred Qualifications Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing. Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures. Requirements Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing. Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.

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