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Senior Analytics Engineer Jobs in Utah (NOW HIRING)

MX Technologies, Inc.

Senior Analytics Engineer

Lehi, UT · On-site

$98K - $134K/yr

Job Summary As a Senior Analytics Engineer within the Operational Analytics department, you'll play a key role in transforming complex, raw data into reliable and performant data products that power ...

Publicis Groupe Holdings B.V

Senior Analytics Engineer

Lehi, UT · On-site

$98K - $134K/yr

Learn more at profitero.com Overview Profitero's Data Engineering team is looking for a Senior Analytics Engineer to own the transformation layer between our data ingestion pipelines and our business ...

ARUP

Senior Analytics Engineer

Salt Lake City, UT

$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 ...

Natures Sunshine Products

Analytics Engineer

Lehi, UT · On-site

Partner with business users, analysts, BI developers, and senior data team members to turn business questions into durable analytics solutions. * Follow and contribute to analytics development ...

Nature's Sunshine Products

Analytics Engineer

Lehi, UT · On-site

Partner with business users, analysts, BI developers, and senior data team members to turn business questions into durable analytics solutions. * Follow and contribute to analytics development ...

Nature's Sunshine Products

Analytics Engineer

Lehi, UT · On-site

Partner with business users, analysts, BI developers, and senior data team members to turn business questions into durable analytics solutions. * Follow and contribute to analytics development ...

Gabb Wireless

Marketing Analytics Engineer

Lehi, UT · On-site

$90K - $115K/yr

What You'll Do Analytics Engineering & Data Modeling * Own and extend our SQL data models (primarily dbt) for marketing and business reporting, maintaining clean, well-documented, test-covered code.

Gabb Wireless

Marketing Analytics Engineer

Lehi, UT · On-site

What You'll Do Analytics Engineering & Data Modeling * Own and extend our SQL data models (primarily dbt) for marketing and business reporting, maintaining clean, well-documented, test-covered code.

Gabb Wireless

Marketing Analytics Engineer

Lehi, UT · On-site

What You'll Do Analytics Engineering & Data Modeling * Own and extend our SQL data models (primarily dbt) for marketing and business reporting, maintaining clean, well-documented, test-covered code.

mophie

Director, Analytics

Midvale, UT

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 ...

ZAGG Inc

mophie Director, Analytics

Midvale, UT

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 ...

ZAGG, Inc.

mophie Director, Analytics

Midvale, UT · On-site

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 ...

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All JobsAnalytics Engineer JobsSenior Analytics Engineer JobsSenior Analytics Engineer Jobs in Utah

Senior Analytics Engineer information

See Utah salary details

$54.2K

$115.2K

$167.1K

How much do senior analytics engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for senior analytics engineer in Utah is $115,214.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,100.00 and $130,600.00 per year, depending on experience, location, and employer.

What engineers make $300,000 a year?

Senior Analytics Engineers can earn $300,000 or more annually, especially with extensive experience, advanced skills in data modeling, SQL, and tools like Python or Spark, and working in high-demand industries or companies. Compensation varies based on location, company size, and individual expertise, often including bonuses and stock options.

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 does a senior analytics engineer do?

A senior analytics engineer designs, develops, and maintains data pipelines and analytics solutions to support business decision-making. They work with large datasets, use tools like SQL, Python, or cloud platforms, and often collaborate with data scientists and business teams to ensure data accuracy and accessibility.

How much do senior analytics engineers make?

Senior analytics engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and industry. They often have expertise in data modeling, SQL, and analytics tools like Tableau or Looker, which can influence salary levels.

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.

What engineer makes $500,000 a year?

Senior Analytics Engineers can earn $500,000 or more annually, especially with extensive experience, advanced skills in data modeling, SQL, and cloud platforms, and roles in high-paying industries or companies. Such compensation often includes base salary, bonuses, and stock options, typically in senior or executive-level positions.

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 are the most commonly searched types of Analytics Engineer jobs in Utah? The most popular types of Analytics Engineer jobs in Utah are:
What are popular job titles related to Senior Analytics Engineer jobs in Utah? For Senior Analytics Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Senior Analytics Engineer jobs in Utah look for? The top searched job categories for Senior Analytics Engineer jobs in Utah are:
What cities in Utah are hiring for Senior Analytics Engineer jobs? Cities in Utah with the most Senior Analytics Engineer job openings:
Senior Analytics Engineer jobs near you
Senior Analytics Engineer

Senior Analytics Engineer

MX Technologies, Inc.

Lehi, UT

Other

Re-posted 24 days ago

Job description

Job Summary

As a Senior Analytics Engineer within the Operational Analytics department, you'll play a key role in transforming complex, raw data into reliable and performant data products that power insights across MX. You'll combine deep technical expertise in SQL, data modeling, and cloud-based data warehouses (such as Google BigQuery) with a strong sense of data stewardship, ensuring accuracy, accessibility, and trust in the analytics that drive business and product decisions.

This role is ideal for a data professional who thrives at the intersection of engineering and analytics-someone who can architect and maintain scalable data models, enforce high standards for data quality, and collaborate closely with cross-functional partners to enable data-driven decisions. As a trusted internal expert, you'll lead by example through mentorship, documentation, and process innovation, helping elevate data practices across the organization.

Job Duties

  • Data Stewardship:
    Design, build, and maintain data pipelines and models that transform raw data into reliable, production-ready datasets. Manage and document data definitions, lineage, and transformations using GitLab or similar tools.

  • Data Quality and Governance:
    Establish and monitor data quality tests to ensure completeness, accuracy, and consistency. Partner with business stakeholders, IT, and data engineering teams to define and enforce governance standards.

  • Data Accessibility and Democratization:
    Develop intuitive, business-friendly data models and assets optimized for analytics. Ensure the right data is available to the right people at the right time, empowering self-service analytics and operational reporting.

  • Feature Store and Data Product Development:
    Curate and maintain high-value datasets and features in the Feature Store to support analytical and machine learning use cases. Track usage metrics and continually optimize for performance and impact.

  • Collaboration and Mentorship:
    Partner cross-functionally with analysts, engineers, and product teams to define data requirements, identify opportunities for process improvements, and align on strategic priorities. Provide mentorship and technical guidance to junior team members.

  • Continuous Improvement:
    Stay current with emerging technologies, tools, and trends in analytics engineering, cloud computing, and data governance. Lead or contribute to initiatives that improve scalability, efficiency, and reliability of MX's data ecosystem.

Requirements

  • Education:
    Bachelor's degree required, preferably in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.

  • Experience:
    Minimum 5 years of experience in analytics engineering, data engineering, or business intelligence roles, with a proven track record of designing and delivering reliable, high-performance data products at scale.

  • Technical Skills:

    • Expert-level SQL proficiency (including advanced window functions, CTEs, subqueries, and query optimization).

    • Strong understanding of dimensional modeling, star/snowflake schemas, and SCD management.

    • Proficiency with cloud data warehouses (Google BigQuery preferred; Snowflake, Redshift, or Databricks acceptable).

    • Familiarity with programming languages such as Python for workflow automation and data quality checks.

    • Experience with modern data versioning and collaboration tools (Git, CI/CD pipelines).

    • Understanding of data governance, lineage, and cataloging tools (e.g., dbt, Dataform, or equivalent).

  • Professional Skills:

    • Proven ability to collaborate cross-functionally and communicate complex data concepts to non-technical audiences.

    • Strong analytical and problem-solving skills, with keen attention to detail and system-level thinking.

    • Demonstrated adaptability and perseverance in fast-paced, evolving environments.

    • Commitment to quality, transparency, and building trust through reliable data products.

    • Track record of mentoring peers and contributing to the growth of data capabilities within an organization.

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