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Python Data Analyst Jobs in Utah (NOW HIRING)

YOUR ROLE The Data Analyst is a key early member of Stio's Data & Analytics team, working alongside ... Review and harden AI-generated SQL, dbt models, and Python code with the judgment to catch issues ...

Experience in SQL, Python, and/or R for querying and analyzing data. AI tool utilization is also a plus. * Understanding of data analysis concepts, statistical methods, and reporting best practices.

Title: Sales Ops Data Analyst In Office /Remote: /Hybrid Exempt / Non-exempt Based: Manila ... Use Python/R and VBA to create and send regular performance reports, focusing on backlog/billing ...

Advanced SQL skills and/or knowledge with Python or R for data analysis and automation * Experience in Guidewire or other modern policy administration systems * Experience working with different ...

Senior Data Analyst

Murray, UT · On-site +1

$80K - $101K/yr

Strong proficiency in data analysis tools such as SQL and programming languages such as Python or R, with demonstrated ability to write efficient queries and build reproducible data pipelines to ...

Data Analyst - Medical Economics

Murray, UT · On-site

$44.36 - $69.85/hr

Advanced healthcare analytics (SQL, Python, Tableau) * Data visualization and management reporting * Cross-functional collaboration and project leadership * Effective verbal, written, and ...

Perform complex data analysis, statistical modeling, and predictive analytics using SQL, R, and Python. * Build and maintain dashboards, reports, and visualizations in Power BI to ensure clarity ...

Data Analytics Engineer

Ogden, UT

$112K - $134K/yr

Data Analyst Engineer to design, develop, and maintain scalable data solutions that support the ... Proficiency in Python or another analytics/programming language * Understanding of data warehousing ...

Data Analytics Engineer

Ogden, UT · On-site

$112K - $134K/yr

Data Analyst Engineer to design, develop, and maintain scalable data solutions that support the ... Proficiency in Python or another analytics/programming language * Understanding of data warehousing ...

Senior DataBI Analyst

Salt Lake City, UT · On-site

$83K - $105K/yr

... Python scripts and Jupyter notebooks for data extraction, transformation, and automation. Qualifications : Required : • 3-5 years of experience in a data analytics, data engineering, or BI analyst ...

... analytical open banking solutions. Focused in the first instance on affordability/credit ... Workplace Python coding experience, including a good knowledge of the principal Python Data Science ...

Write Python scripts and Jupyter notebooks for data extraction, transformation, and automation ... Ability to maintain focus and concentration while analyzing data, reviewing reports, and performing ...

Data Warehouse Analytics Specialist

Sandy, UT · On-site

$17 - $21.75/hr

This role combines SQL/PYTHON analysis, data warehousing, semantic modeling, business intelligence, data governance, reporting validation, and AI-enabled analytics. The position serves as a bridge ...

Data Warehouse Analytics Specialist

Sandy, UT · On-site

$17 - $21.75/hr

This role combines SQL/PYTHON analysis, data warehousing, semantic modeling, business intelligence, data governance, reporting validation, and AI-enabled analytics. The position serves as a bridge ...

This role combines SQL/PYTHON analysis, data warehousing, semantic modeling, business intelligence, data governance, reporting validation, and AI-enabled analytics. The position serves as a bridge ...

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Python Data Analyst information

See Utah salary details

$31K

$75.2K

$123.8K

How much do python data analyst jobs pay per year?

As of Jul 9, 2026, the average yearly pay for python data analyst in Utah is $75,233.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,900.00 and $88,300.00 per year, depending on experience, location, and employer.

What does a Python Data Analyst do?

A Python Data Analyst leverages the Python programming language to collect, process, and analyze large sets of data. They use tools and libraries like Pandas, NumPy, and Matplotlib to clean data, perform statistical analysis, and create visualizations that help organizations make data-driven decisions. Their role often involves extracting insights from complex datasets, automating data workflows, and communicating findings to stakeholders through reports or dashboards. Python Data Analysts play a crucial part in turning raw data into actionable business intelligence.

How do Python Data Analysts typically collaborate with other departments within an organization?

Python Data Analysts often work closely with teams such as marketing, finance, and product development to provide data-driven insights that inform business decisions. They regularly participate in cross-functional meetings to understand departmental objectives, gather requirements for data analysis, and present their findings in an accessible manner. Effective communication and the ability to translate technical results into actionable recommendations are essential, as analysts often act as a bridge between technical data and non-technical stakeholders.

What is the difference between Python Data Analyst vs Data Scientist?

AspectPython Data AnalystData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentBusiness analytics, reporting, data cleaningAdvanced modeling, predictive analytics, research
Industry UsageFinance, marketing, healthcare, retailTech, finance, research, AI development

While both roles require Python and data analysis skills, Data Scientists typically engage in more complex modeling and machine learning, whereas Python Data Analysts focus on data cleaning, visualization, and reporting to support business decisions.

What Does a Python Data Analyst Do?

As a Python data analyst, you use the Python programming language to develop tools for data mining, analysis, and data visualization. You typically develop a script to meet the specific data needs of your client or employer. Then, you test your code and perform debugging duties before deploying it in a live environment. Some data analysts also have algorithm creation responsibilities. In this case, after creating and testing an algorithm, you use Python with your algorithm to interpret data. You also develop reports to show to your clients or employers, and you may code a web app or interface that clients can use to visualize data sets.

Will AI replace a data analyst?

AI tools can automate routine data processing and analysis tasks, but the role of a data analyst involves interpreting insights, understanding business context, and communicating findings, which require human judgment. Data analysts who develop skills in programming, data visualization, and machine learning can adapt to new technologies and continue to add value in data-driven decision-making.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as SQL, Python, and data visualization, along with practical experience and certifications. Employers value diverse backgrounds and experience, making it possible to start a data analyst career at any age.

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

To thrive as a Python Data Analyst, you need strong analytical skills, a solid grasp of statistics, and proficiency in Python programming, often supported by a degree in data science, mathematics, or a related field. Familiarity with data analysis libraries like pandas and NumPy, visualization tools such as Matplotlib or Seaborn, and experience with data querying languages like SQL are typically required. Attention to detail, critical thinking, and effective communication help you derive insights and present findings clearly to stakeholders. These skills and qualities are vital for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

Is Python a high paying job?

Python Data Analysts are generally well-compensated due to their technical skills in programming, data manipulation, and analysis. Salaries vary based on experience, location, and industry, but proficiency in Python often leads to higher earning potential compared to many other entry-level roles in data analysis. Certifications and knowledge of related tools like SQL or machine learning can further increase salary prospects.

Is Python useful for data analysts?

Python is highly useful for data analysts because it offers powerful libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. It is widely used in the industry for automating tasks, building data pipelines, and performing statistical analysis, making it a valuable skill for the role.
What are the most commonly searched types of Python Data Analyst jobs in Utah? The most popular types of Python Data Analyst jobs in Utah are:
Infographic showing various Python Data Analyst job openings in Utah as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 83% Full Time, 9% Part Time, 1% Temporary, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $75,233 per year, or $36.2 per hour.
Python Data Engineer / API Developer - Salt Lake City, UT - day 1 onsite - Long term

Python Data Engineer / API Developer - Salt Lake City, UT - day 1 onsite - Long term

Inficare Technologies

Salt Lake City, UT • On-site

$48.50 - $67/hr

Full-time

Posted 2 days ago


Job description

Role : Python Data Engineer / API Developer
Location: Salt Lake City Its day 1 onsite
Duration: Long term
Key: Python, PySpark, GCP, API development
Role Overview
We are seeking a highly skilled Python Data Engineer / API Developer with strong hands-on experience in PySpark, cloud-based data engineering on GCP, and API development. The ideal candidate should have expertise in building scalable data pipelines, working with distributed clusters, and developing secure APIs for enterprise-grade applications.
Key Responsibilities
  • Design, develop, and maintain scalable data pipelines for batch and/or real-time processing.
  • Build and optimize PySpark applications running on distributed clusters.
  • Develop secure and scalable Python-based APIs.
  • Work with cloud-native GCP services including BigQuery, Composer, DAGs, and Cloud Storage Buckets.
  • Implement data quality checks, validations, and monitoring frameworks within pipelines.
  • Collaborate with cross-functional teams including data analysts, BI teams, and platform engineers.
  • Ensure performance optimization, reliability, and security best practices across solutions.

Required Skills & Qualifications
  • Strong hands-on experience with PySpark and distributed cluster computing.
  • Proven experience in building Python APIs with a focus on security and scalability.
  • Strong knowledge of API frameworks such as FastAPI or Flask.
  • Hands-on experience with Google Cloud Platform (GCP) services:
    • BigQuery
    • Composer
    • DAG orchestration
    • Cloud Storage Buckets
  • Experience in building robust batch and/or real-time data pipelines.
  • Strong understanding of data quality frameworks and practices.

Preferred Skills
  • Experience with BI and reporting tools such as:
    • Power BI
    • MicroStrategy
  • Familiarity with CI/CD pipelines and DevOps practices is an added advantage.
  • Exposure to data governance and monitoring tools is a plus.