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Senior Analytics Engineer Jobs in Bountiful, UT (NOW HIRING)

Senior Analytics Engineer

Salt Lake City, UT · On-site

$100K - $138K/yr

The Sr. Analytics Engineer is responsible for modeling our complex clinical and operational data into data products that capture how a world-class laboratory functions. Works with Information ...

Direct and manage a small team of contractors: an Analytics Engineer responsible for data pipeline ... Work closely with the Sr. Director of Performance Marketing to align measurement frameworks with ...

Direct and manage a small team of contractors: an Analytics Engineer responsible for data pipeline ... Work closely with the Sr. Director of Performance Marketing to align measurement frameworks with ...

Direct and manage a small team of contractors: an Analytics Engineer responsible for data pipeline ... Work closely with the Sr. Director of Performance Marketing to align measurement frameworks with ...

The SVP, Consumer Bank Analytics is responsible for leading the analytics data strategy and insight ... Partner with Technology, Data Engineering, and Enterprise Data teams to improve data accessibility ...

Senior-Level Radiation Analysis Engineer Draper is an independent, nonprofit research and development company headquartered in Cambridge, MA. The 2,000+ employees of Draper tackle important national ...

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Senior Analytics Engineer information

See Bountiful, UT salary details

$56.1K

$119.3K

$173K

How much do senior analytics engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for senior analytics engineer in Bountiful, UT is $119,302.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $135,300.00 per year, depending on experience, location, and employer.

What is a senior analytics engineer?

A Senior Analytics Engineer is a data professional who bridges the gap between data engineering and data analysis. They design, build, and maintain data pipelines, data models, and analytics infrastructure to ensure that data is reliable, accessible, and well-structured for analysis. Typically, they work with tools like SQL, dbt, and cloud data warehouses, collaborating closely with data analysts and business stakeholders to deliver actionable insights. Their role often involves optimizing data workflows, implementing best practices, and mentoring junior team members.

What is the difference between Senior Analytics Engineer vs Data Engineer?

AspectSenior Analytics EngineerData Engineer
Required CredentialsBachelor's/Master's in CS, Analytics, or related; SQL, Python, data visualization skillsBachelor's/Master's in CS, Data Engineering, or related; SQL, Python, ETL tools skills
Work EnvironmentFocus on data analysis, reporting, and insights; collaborates with data teams and business unitsFocus on data pipeline development, infrastructure, and storage; works closely with data infrastructure teams
Employer & Industry UsageUsed across tech, finance, healthcare, and retail for analytics rolesCommon in tech, finance, and data-driven industries for building data systems

While both roles require strong SQL and Python skills, Senior Analytics Engineers primarily focus on analyzing data, creating reports, and deriving insights for business decisions. Data Engineers build and maintain the data infrastructure, pipelines, and storage systems. The roles often collaborate but serve different functions within data teams.

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

To thrive as a Senior Analytics Engineer, you need strong expertise in data modeling, SQL, data warehousing, and analytics, typically backed by a degree in computer science, mathematics, or a related field. Proficiency with tools such as dbt, Python, cloud data platforms (like Snowflake or BigQuery), and experience with BI tools are commonly required, along with certifications in analytics or cloud technologies being a plus. Excellent problem-solving, communication, and stakeholder management skills help you translate business requirements into robust data solutions. These skills ensure data integrity, drive actionable insights, and support effective decision-making across the organization.

How does a senior analytics engineer typically collaborate with data scientists and business stakeholders?

Senior Analytics Engineers play a vital role in bridging the gap between raw data and actionable insights. They work closely with data scientists to ensure that data pipelines and models are robust, scalable, and well-documented. Additionally, they frequently meet with business stakeholders to understand reporting needs and translate them into technical requirements, ensuring that analytics solutions align with organizational goals. This collaborative approach helps maintain data quality and accelerates the delivery of meaningful analyses across teams.
What job categories do people searching Senior Analytics Engineer jobs in Bountiful, UT look for? The top searched job categories for Senior Analytics Engineer jobs in Bountiful, UT are:
What cities near Bountiful, UT are hiring for Senior Analytics Engineer jobs? Cities near Bountiful, UT with the most Senior Analytics Engineer job openings:
Infographic showing various Senior Analytics Engineer job openings in Bountiful, UT as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $119,302 per year, or $57.4 per hour.

Full-time

Posted 23 days ago


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.