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Data Engineer Jobs in Utah (NOW HIRING)

Senior Data Engineer

American Fork, UT · On-site

$94K - $128K/yr

ABOUT THIS ROLE As Senior Data Engineer, you will own and evolve LVT's core data platform-architecting and operating the pipelines, transformations, and semantic models that power reporting ...

Senior Data Engineer

Salt Lake City, UT · On-site

$103K - $140K/yr

Hughes is seeking a Senior Data Engineer to support and evolve our enterprise analytics platform. This role is responsible for designing, building, and maintaining scalable data pipelines and ...

New

Senior Data Engineer

American Fork, UT

$94K - $128K/yr

ABOUT THIS ROLE As Senior Data Engineer, you will own and evolve LVT's core data platform--architecting and operating the pipelines, transformations, and semantic models that power reporting ...

Senior Data Engineer

American Fork, UT · On-site

$94K - $128K/yr

ABOUT THIS ROLE As Senior Data Engineer, you will own and evolve LVT's core data platform-architecting and operating the pipelines, transformations, and semantic models that power reporting ...

Data Engineer IV - AI & Data Products

Draper, UT · On-site

$107K - $128K/yr

Data Engineer IV - AI & Data Products (Draper UT, In-Office) Upbound Group, Inc. (NASDAQ: UPBD) is a technology and data-driven leader in accessible and inclusive financial solutions that address the ...

Senior Big Data Engineer

Salt Lake City, UT · On-site

$54 - $71.25/hr

Responsibilities • Participate in the engineering and administration of big data systems. • Apache Storm/Java development for both data transformation and augmentation. • Employ best practices ...

Software Engineer, Data

Lehi, UT · On-site

$107K - $129K/yr

As a Software Engineer, Data , you will be the core engineer responsible for building, scaling, and optimizing the data infrastructure that transforms raw events into high-fidelity, actionable ...

Software Engineer, Data

Lehi, UT

$107K - $129K/yr

As a Software Engineer, Data , you will be the core engineer responsible for building, scaling, and optimizing the data infrastructure that transforms raw events into high-fidelity, actionable ...

Software Engineer, Data

Lehi, UT

$107K - $129K/yr

As a Software Engineer, Data , you will be the core engineer responsible for building, scaling, and optimizing the data infrastructure that transforms raw events into high-fidelity, actionable ...

Senior Data Engineer

South Jordan, UT · On-site

$100K - $137K/yr

Strong ETL Experience (especially in extraction and ingestion of 3rd party data) Nice-to-haves: * Familiarity with machine learning concepts * Familiarity with asynchronous programming Benefits Key ...

Senior Data Engineer, DX

Magna, UT · On-site +1

$103K - $140K/yr

DX collects millions of data points daily, powering insights into developer productivity and experience at companies like Pinterest, GitHub, BNY, Xero, and many more. Our business has scaled ...

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Showing results 41-60

Data Engineer information

See Utah salary details

$40.5K

$118.1K

$161.6K

How much do data engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for data engineer in Utah is $118,090.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,200.00 and $125,200.00 per year, depending on experience, location, and employer.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

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

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipelines. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience and proficiency with tools like SQL, Python, and cloud platforms.

What are the most commonly searched types of Data Engineer jobs in Utah?

The most popular types of Data Engineer jobs in Utah are:

What are popular job titles related to Data Engineer jobs in Utah?

For Data Engineer jobs in Utah, the most frequently searched job titles are:

What cities in Utah are hiring for Data Engineer jobs?

Cities in Utah with the most Data Engineer job openings:

What are popular job titles related to Data Engineer jobs in UT?

For Data Engineer jobs in UT, the most frequently searched job titles are:

Infographic showing various Data Engineer job openings in Utah as of August 2026, with employment types broken down into 1% As Needed, 66% Full Time, 20% Part Time, and 13% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $118,090 per year, or $56.8 per hour.

Senior Data Engineer

LVT

American Fork, UT • On-site

$94K - $128K/yr

Full-time

Re-posted 13 days ago


Job description

ABOUT THIS ROLE

As Senior Data Engineer, you will own and evolve LVT's core data platform-architecting and operating the pipelines, transformations, and semantic models that power reporting, analytics, and business decisions at scale. This is a high-impact individual contributor role: your technical decisions will influence company-wide systems and competitive positioning, not just team-level outputs. You'll lead cross-functional data initiatives, set engineering standards, and contribute to the data infrastructure that supports LVT's growing AI capabilities.

This role is based in-office out of our Headquarters in American Fork, Utah.

ROLE RESPONSIBILITIES
  • Design, build, and maintain scalable, production-grade ELT pipelines that move data reliably from diverse source systems into a clean, well-governed data platform.

  • Architect and own LVT's Snowflake environment-performance tuning, dynamic tables, clustering strategies, storage optimization, and cost governance.

  • Develop and enforce semantic models that expose consistent, trusted business definitions across all reporting and analytics surfaces.

  • Define and drive data engineering standards that improve quality, reliability, and productivity across teams-not just within BI.

  • Lead cross-functional data initiatives, partnering with engineering, finance, operations, and product to deliver solutions that drive meaningful organizational outcomes.

  • Establish data quality infrastructure-implement validation, monitoring, and alerting frameworks that surface problems before they reach stakeholders.

  • Contribute to AI data infrastructure-support RAG pipelines, vector storage, and Snowflake Cortex integrations as one component of the broader engineering scope.

  • Mentor junior engineers and build strong partnerships with executives and business stakeholders to drive adoption of data solutions.

OUR IDEAL CANDIDATE
  • Seasoned Data Engineer: 7+ years building and operating production data pipelines using SQL, Python, and modern ELT tooling (dbt, Fivetran, Airflow, or equivalents). You've owned systems under pressure and know how to build for long-term reliability.

  • Snowflake Depth: Expert-level Snowflake experience-performance optimization, dynamic tables, data security, and Cortex familiarity. You know when and why to use each capability.

  • Semantic Modeling Ownership: Proven ability to design and maintain semantic or metrics layers that enforce consistent business logic across a complex, multi-team organization.

  • High-Impact Execution: You operate at the level of organizational strategy-your work influences competitive positioning, not just sprint delivery. You define standards, evaluate trade-offs, and build for the long term.

  • Data Quality Obsession: Reliability is non-negotiable. You instrument pipelines with observability, validation, and alerting from day one, and you define the standards others follow.

  • Leadership & Ownership: You own work from scoping through production and beyond. You influence company-wide technology decisions and mentor others along the way-without waiting to be told what to do.

  • AI Infrastructure Fluency: Familiar with AI/ML data patterns-RAG architectures, vector stores, embedding pipelines-and able to build the data infrastructure those systems require.

  • Executive Communication: You build partnerships with executives and cross-functional stakeholders, translating complex technical trade-offs into clear recommendations that earn trust and drive adoption.