1

Databricks Software Jobs in Utah (NOW HIRING)

Staff Data Architect

Lehi, UT · On-site

$59.75 - $77/hr

You'll partner closely with our Staff Software Architect to drive the technical direction of our ... Deep expertise in Databricks (Delta Lake, Unity Catalog) or a comparable modern cloud data platform ...

New

next page

Showing results 1-20

Databricks Software information

What is Databricks software?

Databricks Software is a unified analytics platform built on Apache Spark that provides tools for big data processing, machine learning, and collaborative data science. It enables organizations to store, manage, and analyze large datasets efficiently, supporting both batch and streaming data workloads. Databricks also offers collaborative notebooks, automated workflows, and integrations with cloud storage and data lakes, making it a popular choice for data engineering, data science, and business analytics teams.

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

To thrive as a Databricks Software Engineer, you need strong programming skills in languages like Python, Scala, or Java, as well as a solid understanding of distributed computing and data engineering concepts. Familiarity with Databricks platform, Apache Spark, cloud services (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly valued. Excellent problem-solving abilities, collaboration, and effective communication are important soft skills for this role. These skills ensure efficient development, deployment, and optimization of big data solutions that drive business insights and innovation.

What are some common challenges faced by Databricks software engineers, and how can they be overcome?

Databricks Software Engineers often encounter challenges related to scaling big data pipelines, optimizing Spark workloads, and integrating diverse data sources. Navigating the complexity of distributed systems and managing cloud infrastructure can be demanding, especially when ensuring data reliability and security. To overcome these challenges, engineers typically collaborate closely with data scientists, DevOps, and platform teams, leverage Databricks' extensive documentation and community support, and adopt best practices such as version control and continuous integration. Regular knowledge sharing and staying updated with new features also help engineers succeed in this dynamic environment.

What is the difference between Databricks Software vs Data Engineer?

AspectDatabricks SoftwareData Engineer
Primary RolePlatform for data analytics and machine learningBuilds, maintains data pipelines and infrastructure
Required SkillsSQL, Spark, cloud platforms, data science basicsSQL, ETL, programming (Python, Scala), database management
Work EnvironmentCloud-based, collaborative data platformData teams, cloud or on-premises environments
CertificationsDatabricks certifications, cloud certificationsNone specific, often cloud or data certifications

While Databricks Software provides a platform for data analytics and machine learning, Data Engineers focus on building and maintaining data pipelines and infrastructure. Both roles often work together but have distinct responsibilities and skill sets within the data ecosystem.

What job categories do people searching Databricks Software jobs in Utah look for?

The top searched job categories for Databricks Software jobs in Utah are:

What cities in Utah are hiring for Databricks Software jobs?

Cities in Utah with the most Databricks Software job openings:

Infographic showing various Databricks Software job openings in Utah as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Senior Data Engineer (Databricks & Cloud Analytics

Judge Group, Inc.

Salt Lake City, UT • On-site

$60 - $65/hr

Other

Re-posted yesterday


Job description

Location: Salt Lake City, UT Salary: $60.00 USD Hourly - $65.00 USD Hourly Description:
About the Role
We are seeking an experienced Senior Data Engineer to design, develop, and support enterprise-scale data solutions that enable analytics, reporting, and business decision-making. In this role, you will collaborate with solution architects, business analysts, data scientists, and stakeholders to build scalable cloud-based data platforms and high-performance data pipelines using modern data engineering technologies. The position requires expertise in Databricks, Apache Spark, cloud analytics platforms, and enterprise data integration within an Agile development environment.
Responsibilities
  • Design, develop, test, deploy, and maintain enterprise data engineering solutions using cloud and big data technologies.
  • Design and implement scalable ETL/ELT pipelines utilizing Databricks, Apache Spark (PySpark), Delta Lake, and Azure Data Factory.
  • Build and maintain high-performance data ingestion, transformation, and integration frameworks for analytics and reporting.
  • Develop, optimize, and maintain complex SQL queries, stored procedures, and data transformation processes.
  • Design and implement scalable data models supporting business intelligence, analytics, and AI initiatives.
  • Build and integrate RESTful APIs, event-driven architectures, and SOAP-based services to support enterprise data exchange.
  • Develop and maintain streaming and messaging solutions using Apache Kafka.
  • Monitor, troubleshoot, and optimize production data pipelines, perform root cause analysis, and implement long-term solutions.
  • Apply data quality, governance, security, and performance best practices across data platforms.
  • Manage source code using Git and follow CI/CD and DevOps practices.
  • Collaborate with cross-functional teams to translate business requirements into technical solutions.
  • Participate in Agile ceremonies including sprint planning, backlog refinement, architecture discussions, code reviews, and retrospectives.
  • Create technical documentation, deployment artifacts, testing documentation, and operational runbooks.
  • Mentor junior engineers and contribute to engineering standards, best practices, and continuous improvement initiatives.

Qualifications
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical discipline, or equivalent professional experience.
  • 6+ years of experience designing, developing, and supporting enterprise data platforms, cloud analytics solutions, or large-scale data engineering initiatives.
  • Strong hands-on experience with:
    • Databricks, Apache Spark (PySpark), Python, SQL, Scala
  • Experience with the Databricks ecosystem, including:
    • Databricks Workspaces, Delta Lake, Unity Catalog, Delta Live Tables (DLT), Databricks SQL, MLflow, Databricks Jobs
  • Strong SQL development skills, including query optimization and performance tuning.
  • Experience designing and implementing ETL/ELT solutions using Azure Data Factory or similar cloud integration platforms.
  • Experience with Apache Kafka or other event streaming technologies.
  • Experience integrating enterprise applications using REST APIs, JSON, XML, and SOAP web services.
  • Experience with Azure Data Lake Storage (ADLS Gen2) or comparable cloud storage platforms.
  • Experience using Git for source code management and collaborative software development.
  • Experience working in Linux environments, including shell scripting and command-line utilities.
  • Strong analytical, troubleshooting, and problem-solving skills.
  • Experience working in Agile environments utilizing Scrum, Kanban, or SAFe methodologies.
  • Demonstrated ability to manage multiple priorities while delivering high-quality solutions.
  • Proven ability to work independently while mentoring team members and contributing to technical leadership.
  • Ability to communicate complex technical concepts to both technical and non-technical audiences.
  • Ability to collaborate effectively with cross-functional teams and stakeholders.

Preferred Skills
  • Infrastructure as Code (IaC) tools such as Terraform.
  • CI/CD pipeline implementation using Azure DevOps, GitHub Actions, or similar platforms.
  • Microsoft Azure cloud services.
  • Azure Synapse Analytics.
  • Microsoft Fabric.
  • Power BI.
  • Data governance and metadata management.
  • DataOps and MLOps practices.
  • Enterprise data warehousing.
  • Master Data Management (MDM).
  • Experience working with financial services or public sector data environments.

By providing your phone number, you consent to: (1) receive automated text messages and calls from the Judge Group, Inc. and its affiliates (collectively "Judge") to such phone number regarding job opportunities, your job application, and for other related purposes. Message & data rates apply and message frequency may vary. Consistent with Judge's Privacy Policy, information obtained from your consent will not be shared with third parties for marketing/promotional purposes. Reply STOP to opt out of receiving telephone calls and text messages from Judge and HELP for help.
Contact:
This job and many more are available through The Judge Group. Please apply with us today!