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Data Analytics Jobs in Riverton, UT (NOW HIRING)

Role Overview The Manager of Data Analytics will play a key role in executing Filevine's data and analytics initiatives. Reporting directly to executive leadership, this individual will manage daily ...

New

Role Overview The Manager of Data Analytics will play a key role in executing Filevine's data and analytics initiatives. Reporting directly to executive leadership, this individual will manage daily ...

New

Role Overview The Manager of Data Analytics will play a key role in executing Filevine's data and analytics initiatives. Reporting directly to executive leadership, this individual will manage daily ...

New

Financial Data Analytics Manager

Midvale, UT ยท On-site

$99K - $130K/yr

This Data Analytics Manager will own the strategy, delivery, modernization, and reliable operation of critical data products supporting regulatory reporting, liquidity and balance-sheet management ...

New

This is a remote role that is part of the Finance department and reports to the Director of Data & Analytics. YOUR RESPONSIBILITIES * Partner directly with stakeholders across the business (Product ...

This is a remote role that is part of the Finance department and reports to the Director of Data & Analytics. YOUR RESPONSIBILITIES * Partner directly with stakeholders across the business (Product ...

AVA Consulting is seeking a Data Analyst Location: Salt Lake City, UT (Hybrid) U.S. Citizens and ... Analytics across various domains is undergoing a fundamental shift, and we are looking for a highly ...

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Data Analytics information

See Riverton, UT salary details

$23

$52

$91

How much do data analytics jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for data analytics in Riverton, UT is $52.82, according to ZipRecruiter salary data. Most workers in this role earn between $42.45 and $59.86 per hour, depending on experience, location, and employer.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

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

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data scientist, data engineer, or reporting specialist. They analyze data to help organizations make informed decisions, often using tools like Excel, SQL, and visualization software, and may require knowledge of statistical methods and programming languages like Python or R.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, often requiring proficiency in tools like Excel, SQL, and Python, and may require relevant certifications or a strong understanding of statistical methods.

What are the most commonly searched types of Data Analytics jobs in Riverton, UT?

The most popular types of Data Analytics jobs in Riverton, UT are:

What job categories do people searching Data Analytics jobs in Riverton, UT look for?

The top searched job categories for Data Analytics jobs in Riverton, UT are:

What cities near Riverton, UT are hiring for Data Analytics jobs?

Cities near Riverton, UT with the most Data Analytics job openings:

Infographic showing various Data Analytics job openings in Riverton, UT as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $109,872 per year, or $52.8 per hour.

Manager, Data Analytics

Filevine

Salt Lake City, UT โ€ข On-site

Full-time

Medical, Dental, Vision

Posted 2 days ago

New


Job description

Filevine is a Legal AI company delivering Legal Operating Intelligence for the future of legal work. Grounded in a singular system of truth, Filevine brings together data, documents, workflows, and teams into one unified platform-where modern legal work happens with clarity and consistency.
Powered by LOIS, the Legal Operating Intelligence System, Filevine connects context across every matter to transform legal operations from reactive to proactive. LOIS reads, understands, and reasons across your data to surface insight, automate complexity, and give professionals the clarity and confidence to see more, know more, and do more. Fueled by a team of exceptional collaborators and innovators, Filevine's rapid growth has earned AI awards and recognition from Deloitte and Inc. as one of the most innovative and fastest-growing technology companies in the country.
Role Overview
The Manager of Data Analytics will play a key role in executing Filevine's data and analytics initiatives. Reporting directly to executive leadership, this individual will manage daily analytics operations, deliver corporate metrics, and produce actionable insights to support operational excellence and strategic decision-making across the organization. This position requires a balance of strong technical proficiency, business acumen, and solid communication skills. The ideal candidate will be a hands-on analytical practitioner who can design and deliver high-quality analyses while engaging confidently with executive stakeholders.
Responsibilities:
  • Work closely with the CEO on ad-hoc or other impromptu projects, providing rapid analytical support and insights.
  • Lead daily operations for the corporate analytics function, overseeing the development and delivery of executive-level dashboards, KPIs, and routine reporting.
  • Manage and mentor data analysts, supporting their technical growth and fostering a culture of accuracy, accountability, and continuous improvement.
  • Partner with functional leaders to identify and interpret key trends across product usage, customer health, financial performance, and organizational initiatives.
  • Conduct complex analyses that inform strategic priorities and operational decisions.
  • Build and maintain robust data pipelines and models within Domo, integrating data from Salesforce, Snowflake, HubSpot, the Filevine Platform, and other enterprise systems.
  • Ensure data integrity, consistency, and precision across all reporting outputs.
  • Implement frameworks for tracking key SaaS metrics and KPIs, including ARR, GRR, NRR, churn, customer engagement, and retention.
  • Communicate findings clearly to both technical and non-technical audiences, translating complex data into actionable business insights.
  • Partner cross-functionally with Finance, Operations, Product, and Customer Success teams to align analytics outputs with organizational goals.

Qualifications:
  • Bachelor's degree in Data Analytics, Statistics, Business, Economics, or a related field.
  • 4-6+ years of experience in data analytics or business intelligence, with experience leading or mentoring junior analysts/projects.
  • Demonstrated ability to guide projects and support team development.
  • Expertise in SQL and hands-on experience working with large, complex data environments.
  • Strong proficiency with Domo or equivalent BI tools (e.g., Tableau, Power BI, Looker).
  • Solid understanding of Salesforce data structures and data integration practices.
  • Familiarity with SaaS business models and key financial metrics.
  • Strong communication skills with the ability to effectively present insights to senior stakeholders.
  • High attention to detail, with a commitment to accuracy, data governance, and analytical rigor.

Filevine is an Equal Opportunity Employer. Qualifications for employment, promotion and other terms and conditions of employment are based upon the ability to perform the job. Equal-employment opportunities are provided to all applicants and employees without regard to race, creed, religion, color, age, national origin, sex, disability, veteran status, or other legally protected class. Filevine is committed to providing reasonable accommodations for qualified individuals with disabilities. If you need assistance or accommodation due to disability, or if you have concerns related to Filevine's equal employment opportunities, you may contact us at [email protected]
Cool Company Benefits:
- A dynamic, rapidly growing company, focused on helping organizations thrive
- Medical, Dental, & Vision Insurance (for full-time employees)
- Competitive & Fair Pay
- Maternity & paternity leave (for full-time employees)
- Short & long-term disability
- Opportunity to learn from a dedicated leadership team
- Top-of-the-line company swag
Privacy Policy Notice
Filevine will handle your personal information according to what's outlined in our Privacy Policy.
Communication about this opportunity, or any open role at Filevine, will only come from representatives with email addresses using "filevine.com". Other addresses reaching out are not affiliated with Filevine and should not be responded to.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.