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Dbt Data Engineer Jobs in Utah (NOW HIRING)

Sr. Data Governance Engineer

Draper, UT · On-site

$99K - $134K/yr

Manage relationships with business, product, and engineering data owners * Partner with enterprise ... Familiarity with Databricks, DBT, Snowflake, Claude code, Codex, Windsurfer * Experience with data ...

Senior Analytics Engineer

Salt Lake City, UT · On-site

$100K - $138K/yr

Apply software engineering best practices (version control, modularity, and automated testing, etc) to our data transformation layer using industry-standard frameworks such as dbt. Architect and ...

Senior Analytics Engineer

Salt Lake City, UT · On-site

$100K - $138K/yr

Apply software engineering best practices (version control, modularity, and automated testing, etc) to our data transformation layer using industry-standard frameworks such as dbt. Architect and ...

Senior Analytics Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

Apply software engineering best practices (version control, modularity, and automated testing, etc) to our data transformation layer using industry-standard frameworks such as dbt. Architect and ...

Sr. Technical Product Manager

Lehi, UT · On-site

$161 - $170/hr

... data engineering organizations on data platform initiatives, including familiarity with modern warehouse and transformation tooling such as Snowflake, Databricks, dbt, or similar technologies.

Enterprise Architecture

Ogden, UT · On-site

$130 - $180/hr

Proficiency in modern data platform design -- data lakehouse, streaming architectures (Kafka, Kinesis), Snowflake, Databricks, dbt, and data mesh concepts.* Digital Product Engineering: Hands-on ...

Showing results 41-53

Dbt Data Engineer information

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

To thrive as a Dbt Data Engineer, you need strong SQL skills, experience in data modeling, and a solid understanding of ELT/ETL pipelines, often supported by a degree in computer science or a related field. Familiarity with dbt (data build tool), version control systems like Git, and cloud data platforms such as Snowflake or BigQuery is typically required. Attention to detail, problem-solving abilities, and effective collaboration are essential soft skills for this role. These skills ensure robust, scalable, and maintainable data transformations that drive reliable analytics and business insights.

How does a dbt data engineer typically collaborate with data analysts and other stakeholders?

As a Dbt Data Engineer, you'll work closely with data analysts, business intelligence teams, and sometimes product managers to translate business requirements into reliable, well-structured data models. Collaboration often involves reviewing transformation logic, ensuring data quality, and providing documentation or training on Dbt models. You may also participate in regular stand-ups or data modeling sessions to align on priorities and address data challenges collaboratively. Effective communication skills are key, as you'll bridge the gap between raw data and actionable insights.

What is a dbt data engineer?

Dbt Data Engineers are professionals who specialize in using dbt (data build tool) to transform, test, and document data within modern data warehouses. They build and maintain data pipelines by writing SQL-based transformation scripts and ensuring data quality through automated testing. Dbt Data Engineers collaborate closely with analytics teams to create reliable, well-documented datasets that support business intelligence and analytics initiatives.

What is the difference between Dbt Data Engineer vs Data Analyst?

AspectDbt Data EngineerData Analyst
Primary FocusBuilding and maintaining data transformation pipelines using dbtAnalyzing data to generate reports and insights
Skills & ToolsSQL, dbt, ETL pipelines, cloud platformsSQL, Excel, BI tools, data visualization
Work EnvironmentData engineering teams, cloud data platformsBusiness units, reporting teams
CertificationsSQL, cloud certifications, dbt trainingData analysis, visualization certifications

While both roles work with data and SQL, Dbt Data Engineers focus on developing scalable data transformation pipelines using dbt, whereas Data Analysts primarily analyze data to produce reports and insights. The roles complement each other within data teams but differ in technical scope and responsibilities.

What are popular job titles related to Dbt Data Engineer jobs in Utah? For Dbt Data Engineer jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Dbt Data Engineer jobs? Cities in Utah with the most Dbt Data Engineer job openings:
Infographic showing various Dbt Data Engineer job openings in Utah as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Full-Stack Software Engineer, Platform Data

Zanskar

Salt Lake City, UT

Full-time

Posted 12 days ago


Job description

Role Overview

Title: Full-Stack Software Engineer, Platform Data

Hours: Full-time; salaried

Location: Salt Lake City, UT (on-site, with hybrid flexibility)

Benefits Eligible: Yes

Manager: JD White

Mission – Why we exist and why we need you

Geothermal energy is the most abundant renewable energy source in the world. There is 2,300 times more energy in geothermal heat in the ground than in oil, gas, coal, and methane combined. However, historically it's been hard to find and expensive to develop. At Zanskar, we're using better technology to find and develop new geothermal resources in order to make geothermal a cheap and vital contributor to a carbon-free electrical grid. Joining us means having a direct impact in displacing carbon emissions — and growth opportunities in a startup environment.

The Platform Data team exists to organize all of Zanskar's data — internal, purchased, and public — and transform it into actionable insights. We do that in two ways: we build the data systems and pipelines that bring messy, heterogeneous data into one trustworthy place, and we build the web apps that put that data in front of the geoscientists, engineers, data scientists, and operators who use it to make decisions.

Outcomes - Problems you'll solve

You'll design and operate pipelines that ingest data from many sources — internal systems, purchased datasets, and external feeds — reconciling them into clean, well-modeled, findable data that people trust. You’ll also build the web apps which deliver that data to stakeholders including dashboards, internal applications, and other interfaces. In short, you will be helping create a scalable data ecosystem in keeping with best practices so that geothermal experts can make decisions with confidence.

You'll own features end to end: designing system architecture, pipelines, APIs, and frontends, while being accountable for ensuring the entire system runs smoothly. You'll partner directly with teams across the organization to understand what they're trying to learn from the data, then build the thing that allows them to answer their questions.

Competencies – What we're looking for
  • Full-stack builder: You've built and maintained backend data systems and their associated user-facing applications. You're fluent in Python and SQL on the backend and in TypeScript and React on the frontend. You own features spanning the whole path from source to screen.

  • Data engineering instincts: You've designed schemas and built pipelines that move data reliably from messy sources into clean, queryable form. You think about idempotency, data quality, and what happens when an upstream source changes. Experience with orchestration and warehouse tooling (e.g., Airflow, Dagster, dbt, Snowflake, or BigQuery) is a strong plus. Experience with geospatial or scientific data — raster/vector formats, large file stores, PostGIS, or similar — is also nice-to-have.

  • Product-minded and collaborative: You can sit with a geoscientist, watch where they get stuck, and translate that into shipped products. You treat stakeholders as partners, working comfortably across teams, keeping people in the loop, surfacing trade-offs early, and building alignment on what to build and why.

  • Cloud & infrastructure fluency: You're comfortable deploying and operating what you build on a public cloud (AWS or GCP), with containers (Kubernetes) and infrastructure-as-code (e.g., Pulumi and Terraform).

  • Self-directed and comfortable with unsolved problems: You research options and make recommendations, doing your best work when the problem is real and the constraints are hard. You leverage and delegate to AI, treating modern AI tools as a core part of how you work, handing off tasks to AI agents to use them as a force-multiplier.

Benefits
  • Paid holidays

  • 18 days PTO + PTO accrual increase based on tenure

  • Medical, Dental & Vision coverage

  • Short term and long term disability

  • Equity Packages

  • 401k with matching

  • Paid Parental Leave

Equal Opportunity Employer

Zanskar is an equal-opportunity employer and complies with all applicable federal, state, and local fair employment practice laws.