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Data Analytics Engineer Jobs in Utah (NOW HIRING)

Senior Analytics Engineer

Salt Lake City, UT ยท 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 ...

Data Engineer

Lehi, UT ยท On-site

$107K - $129K/yr

Standardize analytics workflows by integrating software engineering best practices, including version control, CI/CD pipelines, and automated data validation protocols * Develop and refine a robust ...

Data Engineer

Lehi, UT ยท On-site

$107K - $129K/yr

Standardize analytics workflows by integrating software engineering best practices, including version control, CI/CD pipelines, and automated data validation protocols * Develop and refine a robust ...

Data Engineer

Lehi, UT ยท On-site

$107K - $129K/yr

Standardize analytics workflows by integrating software engineering best practices, including version control, CI/CD pipelines, and automated data validation protocols * Develop and refine a robust ...

Data Engineer

Salt Lake City, UT ยท On-site

$110K - $133K/yr

Data Engineer About the Role: We are seeking a Data Engineer to design, build, and optimize data ... You will play a key role in advancing our data analytics capabilities, ensuring data is reliable ...

Data Engineer

Salt Lake City, UT ยท On-site +1

$110K - $133K/yr

Data Engineer About the Role: We are seeking a Data Engineer to design, build, and optimize data ... You will play a key role in advancing our data analytics capabilities, ensuring data is reliable ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and ...

Bachelor's degree in Data Analytics, Statistics, Mathematics, Computer Science, Business Analytics ... Experience with Python, R, or another analytical programming language. * Experience building ...

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Showing results 1-20

Data Analytics Engineer information

See Utah salary details

$40.5K

$118.1K

$161.6K

How much do data analytics engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for data analytics 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.

How do Data Analytics Engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

Can a data engineer make 200k?

Data engineers can earn $200,000 or more annually, especially with experience, advanced skills in cloud platforms, big data tools, and certifications. Salaries vary by location, industry, and company size, with senior roles and those in high-demand markets more likely to reach or exceed this level.

What engineers make $500,000?

Senior data analytics engineers with extensive experience, advanced skills in data modeling, machine learning, and proficiency with tools like Python, SQL, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes equity compensation.

What are the key skills and qualifications needed to thrive as a Data Analytics Engineer, and why are they important?

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

Is 40 too late for data science?

Data Analytics Engineers and data science professionals can successfully transition into the field at age 40 or older, as skills such as programming, statistical analysis, and experience with tools like Python or SQL are valuable regardless of age. Many employers value diverse experience and lifelong learning, and certifications or online courses can help enhance credentials at any age.

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

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and systems to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to deliver actionable insights.
What are the most commonly searched types of Data Analytics Engineer jobs in Utah? The most popular types of Data Analytics Engineer jobs in Utah are:
What job categories do people searching Data Analytics Engineer jobs in Utah look for? The top searched job categories for Data Analytics Engineer jobs in Utah are:
What cities in Utah are hiring for Data Analytics Engineer jobs? Cities in Utah with the most Data Analytics Engineer job openings:
Product Manager, Data & Analytics

Product Manager, Data & Analytics

Nature's Sunshine Products

Lehi, UT โ€ข On-site

Full-time

Re-posted 2 days ago


Job description

About the Role

Nature's Sunshine is entering an ambitious new phase of growth, and data will play a central role in how the company scales. As part of that investment, we are building a new Enterprise Data & Analytics function to unlock trusted data, sharpen decision-making, and help teams improve business performance.

We are looking for a Product Manager to turn business needs into a focused roadmap for analytics products, reporting experiences, KPI adoption, and decision-support capabilities.

This is an analytics product role, not project coordination or report delivery. You will own the why, what, and priority of analytics products while partnering with analytics engineers, BI developers, business leaders, IT, and data governance stakeholders.

What You Will Own
  • Own the analytics product roadmap for assigned business domains or enterprise priorities.
  • Lead intake, discovery, scoping, and prioritization for analytics requests, dashboards, reporting products, and decision-support tools.
  • Make tradeoff recommendations based on business value, urgency, effort, reusability, adoption likelihood, and strategic priority.
  • Translate unclear needs into problem statements, requirements, user stories, acceptance criteria, and success measures.
  • Own backlog artifacts in Azure DevOps, including epics, features, user stories, dependencies, and prioritization context.
  • Partner with business leaders to clarify decision needs, reporting gaps, KPI ownership, and metric definitions.
  • Partner with Data Engineering, Analytics Engineering, and BI Development to translate business priorities into reliable data pipelines, governed metrics, semantic models, reusable data assets, and usable reporting experiences
  • Track adoption, usage, satisfaction, and business impact; reduce duplicate reporting and low-value one-off work.
What We Are Looking ForRequired Qualifications
  • 4+ years of experience in product management, analytics product ownership, business analysis, BI delivery, consulting, or a related role.
  • Proven ability to translate business problems into clear analytics requirements and prioritized delivery plans.
  • Experience working with BI tools, reporting products, KPIs, analytics products, or enterprise data platforms.
  • Strong stakeholder management skills across business, technical, and leadership audiences.
  • Ability to separate the stated request from the underlying business problem and right analytics solution.
  • Sound prioritization judgment across value, urgency, complexity, reusability, and strategic fit.
  • Clear written and verbal communication; comfort operating through ambiguity and competing priorities.
  • Ability to partner with technical teams without personally owning data engineering, semantic modeling, or dashboard development.
Preferred Qualifications
  • Experience with Power BI, Microsoft Fabric, Azure, Snowflake, Databricks, Tableau, Looker, or similar platforms.
  • Experience managing analytics roadmaps, BI backlogs, data product portfolios, or reporting governance processes.
  • Experience using Azure DevOps or a similar tool to manage epics, features, user stories, and acceptance criteria.
  • Experience communicating roadmap decisions, tradeoffs, and delivery status to senior stakeholders.
  • Familiarity with data governance, KPI standardization, semantic models, certified datasets, or enterprise reporting standards.
  • Interest in using AI-assisted workflows to improve discovery, documentation, backlog refinement, stakeholder communication, and product management practices.
Who Will Thrive Here

You will thrive in this role if you like turning messy business needs into clear choices, asking sharp questions, and focusing teams on analytics work that improves decisions.

You should be able to challenge assumptions, redirect low-value requests, and say not yet or not that way with credibility and tact. You do not need to be the deepest technical expert in the room, but you do need enough analytics fluency to understand tradeoffs, dependencies, data quality risks, and adoption barriers.

How Success Will Be Measured
  • Roadmap priorities are clear, visible, and aligned to business needs.
  • Intake and prioritization decisions are transparent and defensible.
  • Analytics products have clear users, owners, success criteria, and lifecycle status.
  • Adoption, usage, and satisfaction improve for priority analytics products.
  • Duplicate, low-value, or poorly defined reporting requests decrease over time

#ZR


Nature's Sunshine is dedicated to being a Force of Nature that champions social and environmental wellness. We are focused on building a team of professionals with diverse backgrounds and experiences to become the natural supplement company of the future. By celebrating the individuality and unique perspectives of our workforce, we empower our employees to share the healing power of nature with more people around the world. And through our commitment to sustainable processes, renewable energy usage and waste reduction initiatives, we're devoted to preserving nature and its power for future generations.

We believe we are stronger together, and our ongoing commitment to diversity, equity, inclusion and belonging ensures that every employee is treated with fairness and respect. Because doing what's right-in the right way-is how we succeed as a company and a society.


Job Posted by ApplicantPro