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Full Time Data Analytics Jobs in Utah (NOW HIRING)

KēSTA I.T.

Data Engineer

Draper, UT · On-site

$100K - $114K/yr

T. is actively seeking a Data Engineer for an immediate full-time opportunity with our industry ... This position partners closely with analysts and data scientists to transform raw data into ...

Jade Global

Data/Ai Engineer Intern

Ogden, UT · On-site

This is not an internship - it's a full-time opportunity with a competitive salary, full benefits ... Analyzing complex data using AI tools and frameworks * Exploring the use of LLMs, computer vision ...

Jade Global

Data/Ai Engineer Intern

Ogden, UT · On-site

This is not an internship - it's a full-time opportunity with a competitive salary, full benefits ... Analyzing complex data using AI tools and frameworks * Exploring the use of LLMs, computer vision ...

Jade Global

Integration Analyst Intern

Ogden, UT

Integration Analyst Intern1 Integration Analyst Intern in the Data & AI Team Launch Your Career ... This is not an internship - it's a full-time opportunity with a competitive salary, full benefits ...

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All JobsData Analytics JobsFull Time Data Analytics JobsFull Time Data Analytics Jobs in Utah

Full Time Data Analytics information

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

To excel in a Full Time Data Analytics role, strong analytical skills, proficiency in mathematics and statistics, and a relevant degree such as in computer science, statistics, or data science are essential. Familiarity with tools like SQL, Python or R, and data visualization platforms such as Tableau or Power BI, as well as knowledge of database management systems, is typically required. Excellent problem-solving abilities, attention to detail, and effective communication skills distinguish top performers in this field. These competencies are crucial for transforming complex data into actionable insights that drive business decisions and strategic growth.

What is the difference between Full Time Data Analytics vs Data Analyst?

AspectFull Time Data AnalyticsData Analyst
CredentialsBachelor's degree in Data Science, Analytics, or related field; certifications like CAP, Microsoft Certified Data AnalystBachelor's degree often required; certifications like CAP or Microsoft Certified Data Analyst are common
Work EnvironmentFull-time employment in corporate, tech, finance, or healthcare sectorsTypically similar; employed full-time in various industries
Employer & Industry UsageUsed by companies seeking ongoing data analysis supportCommonly used by organizations needing data insights and reporting

Full Time Data Analytics and Data Analyst roles often overlap in credentials, work environment, and industry usage. The main difference lies in scope: Full Time Data Analytics may imply a broader or more strategic role, while Data Analyst is more specific to data reporting and analysis tasks.

What are Full Time Data Analytics jobs?

Full Time Data Analytics jobs involve working with data to help organizations make informed business decisions. Professionals in these roles collect, process, and interpret large datasets to identify trends, patterns, and opportunities. They use statistical tools, programming languages, and visualization techniques to turn raw data into actionable insights. These positions typically require strong analytical skills and proficiency in software such as Excel, SQL, Python, or R. Full-time roles generally offer regular working hours and employee benefits.

What are some common challenges faced by professionals in full-time data analytics roles, and how can they be addressed?

One common challenge in full-time data analytics roles is managing large and complex datasets that may contain inconsistencies or missing values. Analysts often need to spend significant time on data cleaning and preprocessing before meaningful analysis can occur. Additionally, communicating technical findings to non-technical stakeholders can be challenging, requiring strong data visualization and storytelling skills. Collaborating closely with business teams and continuously refining communication methods can help address these challenges and increase the impact of analytics work.
What are the most commonly searched types of Data Analytics jobs in Utah? The most popular types of Data Analytics jobs in Utah are:
What cities in Utah are hiring for Full Time Data Analytics jobs? Cities in Utah with the most Full Time Data Analytics job openings:
Full Time Data Analytics jobs near you
Engineer 2 (Full time) - Special Projects Department

Engineer 2 (Full time) - Special Projects Department

The Church of Jesus Christ of Latter-day Saints

Salt Lake City, UT • On-site

Full-time

Posted 14 days ago

Church of Jesus Christ of Latter-day Saints rating

8.5

Company rating: 8.5 out of 10

Based on 78 frontline employees who took The Breakroom Quiz

2nd of 15 rated religious organizations

Job description

The purpose of this position is to "seek to bring forth and establish the cause of Zion."

Design, support, and maintain the engineering systems and data that enable analytics, AI-driven insights, and decision-making across temple construction and operations. This role combines engineering and data/analytics engineering, supporting data pipelines, AI-ready datasets, and business-ready insights in partnership with business operations teams.

Church employees find joy and satisfaction in using their unique talents and abilities to further the Lord's work. From the IT professional who develops an app that sends the gospel message worldwide, to the facilities manager who maintains our buildings- giving Church members places to worship, teach, learn, and receive sacred ordinances-our employees seek innovative ways to share the gospel of Jesus Christ with the world. They are literally working in His kingdom.
Only members of the Church who are worthy of a temple recommend qualify for employment. Apart from this, the Church is an equal opportunity employer and does not discriminate in its employment decisions on any basis that would violate U.S. or local law.
Qualified applicants will be considered for employment without regard to race, national origin, color, gender, pregnancy, marital status, age, disability, genetic information, veteran status, or other legally protected categories that apply to the Church. The Church will make reasonable accommodations for qualified individuals with known disabilities.

  • Bachelor's degree in Engineering or a related field, or equivalent field experience

  • 3-5 years in engineering, with experience in data engineering, analytics engineering, or related work supporting property development and facility operations data

  • Experience working with AI/ML concepts, data preparation for models, or supporting predictive analytics use cases

Technical

  • Agentic AI architecture and orchestration (multi-agent systems, tool/function calling, MCP or comparable agent-to-system protocols) 
  • Autonomous enterprise solution design - workflows where AI agents execute, not just recommend, across business systemsETL/ELT pipeline development (batch and/or streaming) feeding agentic and analytics workloads
  • Governance and guardrails for AI-driven and autonomous systems (data quality, audit trail, human-in-the-loop controls)
  • Exploratory data analysis (EDA), KPI/metric development, and AI-ready dataset preparation

  • Support engineering systems and design processes that generate data for project and property operations

  • Build and maintain data pipelines from project and property systems

  • Support cloud data platforms and data storage environments

  • Organize data to support reporting across assets and projects

  • Combine and structure data from engineering, construction, and operations

  • Create and improve autonomous enterprise dashboards and reports for tracking performance 

  • Work with engineering, construction, and facilities teams to deliver data solutions

  • Ensure data is accurate, consistent, and reliable

  • Improve data processes for speed and efficiency

  • Support lifecycle data tracking (design construction operations maintenance)

  • Establish documentation, standards, and data engineering best practices

  • Prepare clean, usable datasets for analytics and AI use

  • Perform exploratory data analysis to identify trends, anomalies, and insights

  • Help define and standardize key performance metrics (KPIs)

  • Collaborate on predictive and AI use cases 

What Church of Jesus Christ of Latter-day Saints employees say

Pay

Benefits

Hours and flexibility

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