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Dbt Analytics Jobs in Utah (NOW HIRING)

Opiniion

Analytics Platform Developer

Lehi, UT · On-site

$100 - $125/hr

Build and maintain data models in dbt on Databricks, in a version-controlled repository with code review on every change. * Write tests and documentation alongside your models rather than after them.

Gabb Wireless

Marketing Analytics Engineer

Lehi, UT

$90K - $115K/yr

Own and extend our SQL data models (primarily dbt) for marketing and business reporting ... Marketing Analytics & Measurement * Build and maintain dashboards and reports covering core ...

Gabb Wireless

Marketing Analytics Engineer

Lehi, UT · On-site

$90K - $115K/yr

Own and extend our SQL data models (primarily dbt) for marketing and business reporting ... Marketing Analytics & Measurement * Build and maintain dashboards and reports covering core ...

Gabb Wireless

Marketing Analytics Engineer

Lehi, UT · On-site

$100 - $125/hr

Own and extend our SQL data models (primarily dbt) for marketing and business reporting ... Marketing Analytics & Measurement * Build and maintain dashboards and reports covering core ...

Zions Bank

Financial Data Analytics Manager

Midvale, UT · On-site

$99K - $130K/yr

This Financial Data Analytics Manager will own the strategy, delivery, modernization, and reliable ... Banking, Databricks, Python, CI/CD, cloud infrastructure, dbt, and enterprise data governance ...

ARUP

Senior Analytics Engineer

Salt Lake City, UT

$100K - $138K/yr

... frameworks such as dbt. Architect and optimize the query layer to ensure performant analytics ... across our data lake and warehouse using serverless or managed technologies like Athena, Redshift ...

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All JobsDbt Analytics JobsDbt Analytics Jobs in Utah

Dbt Analytics information

See Utah salary details

$34.1K

$58.2K

$83.8K

How much do dbt analytics jobs pay per year?

As of Sep 8, 2026, the average yearly pay for dbt analytics in Utah is $58,176.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,200.00 and $64,600.00 per year, depending on experience, location, and employer.

What is a dbt analytics?

A dbt Analytics job typically refers to a role focused on using dbt (data build tool) to transform, test, and document data within a data warehouse. Professionals in this field design and manage data models, write SQL-based transformations, and ensure data quality for analytics purposes. They collaborate with data engineers and analysts to build efficient, maintainable workflows that support business intelligence and data-driven decision-making. dbt Analytics jobs require strong SQL skills, familiarity with modern data stack tools, and an understanding of data modeling best practices.

What are the key skills and qualifications needed to thrive as a dbt analytics professional?

To thrive as a DBT Analytics professional, you need strong SQL skills, a solid understanding of data modeling, and experience with analytics engineering, typically backed by a degree in a quantitative field. Familiarity with the DBT (Data Build Tool) platform, cloud data warehouses like Snowflake or BigQuery, and version control systems such as Git is essential. Attention to detail, problem-solving abilities, and effective communication help you collaborate with stakeholders and ensure data reliability. These skills and tools are crucial for transforming raw data into actionable insights and maintaining robust, scalable analytics infrastructure.

How does a dbt analytics professional typically collaborate with data engineers and analysts within a team?

Dbt Analytics professionals play a key role in bridging the work of data engineers and data analysts. They transform raw data into clean, well-documented, and analysis-ready datasets using dbt (data build tool), ensuring consistency and reliability. Collaboration often involves working closely with data engineers to understand data sources and pipelines, while also partnering with analysts to tailor data models to business needs. Effective communication and regular feedback loops are crucial, as dbt professionals often serve as the link between technical data infrastructure and business-facing analysis.

What is the difference between Dbt Analytics vs Data Analyst?

AspectDbt AnalyticsData Analyst
Required CredentialsSQL, data modeling, analytics certificationsStatistics, Excel, SQL, sometimes certifications
Work EnvironmentData teams, analytics platforms, cloud environmentsBusiness units, reporting tools, spreadsheets
Industry UsageData transformation, modeling, analytics pipelinesData interpretation, reporting, insights

While Dbt Analytics focuses on transforming and modeling data within analytics workflows, Data Analysts primarily interpret data and generate reports. Both roles require SQL skills and work closely with data teams, but Dbt Analytics emphasizes data transformation using tools like dbt, whereas Data Analysts focus on analyzing and communicating insights.

Is dbt in demand?

Dbt analytics engineers are increasingly in demand as organizations adopt modern data transformation tools to improve data workflows. Skills in SQL, data modeling, and familiarity with cloud platforms enhance job prospects in this field, which is growing alongside the broader data analytics industry.

What are popular job titles related to Dbt Analytics jobs in Utah?

For Dbt Analytics jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Dbt Analytics jobs in Utah look for?

The top searched job categories for Dbt Analytics jobs in Utah are:

What cities in Utah are hiring for Dbt Analytics jobs?

Cities in Utah with the most Dbt Analytics job openings:

Dbt Analytics jobs near you
Infographic showing various Dbt Analytics job openings in Utah as of August 2026, with employment types broken down into 1% Internship, 92% Full Time, 3% Part Time, and 4% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $58,176 per year, or $28 per hour.

Senior Analytics Engineer

Bamboo Insurance

Midvale, UT • On-site

Full-time

Re-posted 24 days ago

Key responsibilities

  • Design, build, validate, and maintain analytical data models and curated datasets for reporting, business intelligence, and operational analytics.

  • Partner with business stakeholders to understand reporting needs, translate requirements into data models, and document business rules and data lineage.

  • Build validation checks, perform data reconciliation, investigate data issues, and support the validation of reports, dashboards, and metrics.

Job description

Role Summary 

We are seeking a strong Analytics Engineer to join our Data Strategy and Architecture team. This role will help design, build, validate, and maintain trusted analytical data assets that support reporting, business intelligence, operational analytics, and executive decision-making. 

The Analytics Engineer will work closely with business stakeholders, data engineers, data architects, analysts, and reporting teams to translate business requirements into scalable data models, curated datasets, and high-quality reporting layers. This is a hands-on technical role requiring strong SQL, data modeling, data validation, and business analysis skills. 

The ideal candidate has experience working in a modern cloud data platform, preferably Snowflake, and understands how to build governed, reusable, and reliable analytical datasets. Experience in Property and Casualty insurance is strongly preferred. 

Key Responsibilities 

Data Modeling and Analytics Engineering 

  • Design, build, and maintain analytical data models for reporting and business consumption.  

  • Develop curated datasets, fact tables, dimension tables, marts, and semantic-ready data layers.  

  • Build scalable transformations using SQL, dbt, Snowflake, or similar modern data tools.  

  • Move complex business logic out of reports and into governed data models.  

  • Support medallion-style data architecture across Bronze, Silver, and Gold layers.  

  • Optimize queries and models for performance, usability, and maintainability.  

Business Requirements and Data Mapping 

  • Partner with business stakeholders to understand reporting needs, KPIs, and data definitions.  

  • Translate business requirements into source-to-target mappings and analytical data models.  

  • Document business rules, transformation logic, metric definitions, data lineage, and known gaps.  

  • Work with business SMEs to clarify ambiguous definitions and resolve data interpretation issues.  

  • Support requirements across Policy, Billing, Claims, Finance, Underwriting, Agency, and Operations domains.  

Data Quality, Testing, and Reconciliation 

  • Build validation checks to ensure data completeness, accuracy, consistency, and traceability.  

  • Perform reconciliation between source systems, data warehouse layers, and BI reports.  

  • Create SQL-based testing scripts, dbt tests, and automated data quality checks.  

  • Investigate data issues and determine whether defects are caused by source data, transformation logic, model design, or reporting logic.  

  • Support UAT and help business users validate reports, extracts, dashboards, and metrics.  

Reporting and BI Enablement 

  • Prepare trusted datasets for BI tools such as Power BI, Tableau, Pyramid, Looker, or similar platforms.  

  • Partner with report developers and analysts to improve report accuracy and performance.  

  • Support executive dashboards, operational reports, financial reporting, and regulatory or audit-related extracts.  

  • Ensure reporting datasets are reusable, well-documented, and aligned with enterprise standards.  

Collaboration and Delivery 

  • Work closely with Data Engineering, Architecture, Business Intelligence, Product, Finance, Claims, and Operations teams.  

  • Participate in Agile delivery, sprint planning, backlog refinement, and release validation.  

  • Communicate data issues, risks, dependencies, and tradeoffs clearly to both technical and business audiences.  

  • Take ownership of assigned models, datasets, defects, and deliverables.  

Required Qualifications 

  • Bachelors or Masters in Finance, Accounting, Economics, Business Administration, Statistics, Mathematics, Computer Science, or Engineering 

  • 5+ years of experience in analytics engineering, data analysis, BI engineering, data warehousing, or a similar data role.  

  • Strong SQL skills, including joins, CTEs, aggregations, window functions, data profiling, reconciliation, and performance tuning.  

  • Experience building analytical data models in Snowflake, or similar cloud data platforms.  

  • Experience with dbt or similar SQL-based transformation frameworks.  

  • Strong understanding of dimensional modeling, fact and dimension design, star schemas, and curated data layers.  

  • Experience translating business requirements into data mappings, transformation logic, and reporting datasets.  

  • Strong data validation, reconciliation, and root-cause analysis skills.  

  • Experience supporting BI tools such as Power BI, Tableau, Pyramid, Looker, or similar.  

  • Ability to work independently with business and technical teams.  

  • Strong communication skills with the ability to explain data issues in clear business terms.  

Preferred Qualifications 

  • Property and Casualty insurance experience strongly preferred.  

  • Experience with Guidewire PolicyCenter, BillingCenter, ClaimCenter, BriteCore, or similar insurance platforms.  

What This Role Is Not 

This is not only a dashboard developer role. 

This is not a pure data engineering pipeline role. 

This is not a business analyst role with light SQL. 

This role requires a strong hybrid profile: SQL depth, data modeling discipline, business understanding, reporting knowledge, testing rigor, and the ability to build reliable analytical data assets in a modern cloud data platform. 

Salary

Starting at $150,000 annually. Candidate's skills, experience and abilities will be taken into consideration for final offer.

Apply