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Senior Analytics Manager Jobs in Utah (NOW HIRING)

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 ... Works with Information Technology Staff, Medical Directors, and Lab Managers to understand the ...

Gong.io

People Analytics Manager

Salt Lake City, UT · On-site +1

$115K - $175K/yr

As the People Analytics Manager, you will empower Gong\'s Leadership Team and broader People ... senior leadership * Analyze large, complex datasets from multiple sources to surface actionable ...

Synchrony

SVP, Consumer Bank Analytics

Draper, UT · On-site

The SVP, Consumer Bank Analytics is responsible for leading the analytics data strategy and insight ... Manage relationships with external data and analytics partners supporting customer intelligence ...

Direct Counsel

Senior Conflicts Analyst

Salt Lake City, UT · On-site +1

$100K - $120K/yr

Direct Counsel is seeking an experienced and detail-oriented Senior Conflicts Analyst to join the conflicts and risk management team at a respected national law firm. This is a high-level opportunity ...

IPL (Indiana)

Senior Analyst, FP&A

Salt Lake City, UT · On-site

$82K - $103K/yr

The Senior Analyst will own the financial reporting cycle end-to-end for an assigned portfolio of ... Identifyfinancial risks and opportunities; partner with asset management and operations to surface ...

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Senior Analytics Manager information

See Utah salary details

$41K

$104.2K

$153.4K

How much do senior analytics manager jobs pay per year?

As of Aug 5, 2026, the average yearly pay for senior analytics manager in Utah is $104,212.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,100.00 and $122,900.00 per year, depending on experience, location, and employer.

What does a senior analytics manager do?

A Senior Analytics Manager leads a team of analysts to interpret data, develop insights, and inform business strategy. They are responsible for overseeing data collection, ensuring data quality, and presenting actionable findings to stakeholders. In addition, they often collaborate cross-functionally with other departments to support decision-making and optimize business processes. Senior Analytics Managers also play a major role in mentoring team members and implementing best practices in data analysis.

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

To thrive as a Senior Analytics Manager, you need advanced analytical skills, a solid background in statistics or data science, and experience leading analytics projects, often supported by a relevant degree. Proficiency in tools such as SQL, Python, R, and business intelligence platforms like Tableau or Power BI, as well as certifications in analytics or data management, is highly valued. Exceptional leadership, communication, and problem-solving abilities help drive team performance and translate data insights into business strategy. These competencies are crucial for delivering actionable insights, influencing decision-making, and ensuring data-driven success across the organization.

What are the main challenges senior analytics managers face when leading cross-functional analytics projects?

Senior Analytics Managers often encounter challenges such as aligning stakeholders from different departments, managing competing priorities, and ensuring data consistency across sources. Effective communication is essential to translate complex analytical insights into actionable strategies that resonate with both technical and non-technical team members. Additionally, they must balance hands-on analytical work with mentoring junior analysts and driving project delivery to meet organizational goals.

What is the difference between Senior Analytics Manager vs Data Analyst?

AspectSenior Analytics ManagerData Analyst
Required CredentialsBachelor's/Master's in Analytics, Statistics, or related field; experience in leadership rolesBachelor's degree in Data Science, Statistics, or related field; entry to mid-level experience
Work EnvironmentLeads teams, manages projects, collaborates with executivesAnalyzes data, prepares reports, supports decision-making
Employer & Industry UsageCommon in corporate, finance, tech sectors for strategic insightsUsed across various industries for data interpretation and reporting

The Senior Analytics Manager typically oversees analytics teams, manages strategic projects, and interacts with leadership, requiring more experience and leadership skills. Data Analysts focus on data collection, analysis, and reporting, often supporting Senior Managers. The roles differ mainly in scope, responsibility, and seniority, but both require strong analytical skills and relevant credentials.

What are popular job titles related to Senior Analytics Manager jobs in Utah? For Senior Analytics Manager jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Senior Analytics Manager jobs in Utah look for? The top searched job categories for Senior Analytics Manager jobs in Utah are:
What cities in Utah are hiring for Senior Analytics Manager jobs? Cities in Utah with the most Senior Analytics Manager job openings:
Senior Analytics Manager jobs near you
Infographic showing various Senior Analytics Manager job openings in Utah as of July 2026, with employment types broken down into 1% Internship, 90% Full Time, 7% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $104,212 per year, or $50.1 per hour.

Senior Analytics Engineer

MX Technologies, Inc.

Lehi, UT • On-site

Other

This job post has expired today. Applications are no longer accepted.

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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