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Data Analyst Github Jobs in Utah (NOW HIRING)

YOUR ROLE The Data Analyst is a key early member of Stio's Data & Analytics team, working alongside ... You'll work in a stack built around Snowflake, Fivetran, dbt, Power BI, GitHub, and increasingly ...

Senior Data Analyst

Murray, UT ยท On-site +1

$80K - $101K/yr

Senior Data Analyst Inside Real Estate is a fast-growing, independently-owned real estate software ... control/database tools (Github). * Experience with experimental design and A/B testing ...

... Github, Kubernates and REST API's experience For data Science/Data Analyst/AI/Machine learning Positions Preferred SKILLS Associate or Bachelors degree or Masters degree in Computer Science, Computer ...

... Azure Synapse Analytics (formerly SQL DW) to create a single source of truth. โ€ข Building ... Jenkins/GitHub/Azure DevOps pipelines โ€ข Strong communication skills โ€ข Strong stakeholder ...

Data Engineer

Woods Cross, UT ยท On-site

$108K - $129K/yr

Develop and maintain clean, reliable datasets for reporting and analytics * Collaborate on data ... Experience using Git for version control (e.g., GitHub), including branching and pull request ...

Data & Infrastructure Engineer

Draper, UT ยท On-site

$107K - $128K/yr

... analytics, and strategic decision-making. You will maintain and extend our data pipelines, API ... Manage version-controlled codebases using GitHub, including code reviews, CI/CD pipelines, and ...

Senior Data Engineer

Provo, UT ยท On-site

$100K - $136K/yr

Design and maintain robust data models to support analytics and self-service BI. Define and ... GitHub, testing, code reviews, and CI/CD for data pipelines. Able to collaborate effectively with ...

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Data Analyst Github information

See Utah salary details

$31K

$75.2K

$123.8K

How much do data analyst github jobs pay per year?

As of Jun 12, 2026, the average yearly pay for data analyst github 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.

How does a Data Analyst at GitHub typically collaborate with engineering and product teams?

At GitHub, Data Analysts frequently work alongside engineering and product teams to translate business questions into actionable data insights. They participate in cross-functional meetings, help define key metrics, and build dashboards or reports tailored to the needs of different stakeholders. Effective collaboration requires strong communication skills, as analysts must explain complex data findings to both technical and non-technical colleagues. This collaborative environment fosters continual learning and often provides opportunities to contribute to strategic decisions that impact the direction of products and features.

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

To thrive as a Data Analyst on GitHub, you need strong analytical skills, experience in statistics, and proficiency in data manipulation using languages like Python or SQL, often backed by a relevant degree. Familiarity with data visualization tools (e.g., Tableau, Power BI), Git version control, and GitHub workflows is essential, and certifications in data analysis or related fields are advantageous. Attention to detail, problem-solving, and effective communication are vital soft skills for collaborating on open-source projects and sharing insights. These competencies enable accurate data-driven decision-making, efficient project collaboration, and impactful contributions to the GitHub community.

What are Data Analysts on GitHub?

Data Analysts on GitHub are professionals or contributors who use the platform to share, collaborate, and manage data analysis projects. They leverage GitHub to store datasets, share scripts and code (often in languages like Python or R), and document their analyses using tools like Jupyter Notebooks or Markdown. GitHub enables Data Analysts to version-control their work, collaborate with others through pull requests and issues, and showcase their portfolios to potential employers or collaborators.

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

AspectData Analyst GithubData Scientist
Required CredentialsBachelor's in Data Analytics, Statistics, or related field; proficiency in SQL, Excel, and visualization toolsBachelor's or Master's in Data Science, Computer Science, or related; knowledge of programming languages like Python or R, machine learning
Work EnvironmentCollaborates with teams to analyze data, create dashboards, and support decision-makingBuilds models, develops algorithms, and performs advanced statistical analysis
Employer & Industry UsageUsed across industries for reporting, data visualization, and business insightsApplied in AI, predictive modeling, and complex data analysis projects

While both roles involve working with data, Data Analyst Github focuses on data visualization, reporting, and supporting business decisions, often using tools like SQL and Excel. Data Scientists perform advanced analytics, build predictive models, and require programming skills in Python or R. The roles overlap in data handling but differ in complexity and technical depth.

What cities in Utah are hiring for Data Analyst Github jobs? Cities in Utah with the most Data Analyst Github job openings:
Data Analyst

Data Analyst

Stio

Salt Lake City, UT โ€ข Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago


Job description

ABOUT US

Stio is an omni-channel mountain brand that designs, develops and sells beautiful, functional, and innovative apparel, footwear and other accessories infused with the soul of the mountain lifestyle. With headquarters in Jackson, Wyoming, Stio draws inspiration from the surrounding Teton Range and offers product via Stio.com, catalog, B2B and its Mountain Studio retail locations.

We live and love mountain life, and as such see ourselves as caretakers of the resources that provide it. We are proud partners of Protect Our Winters and the Conservation Alliance among many other organizations. We have a strong preferred materials platform, use Bluesign approved textiles wherever possible, audit our supply chains for best practices, and operate our workplaces responsibly.

We think that outside is the best side and that you can't improve on nature. It's good for mind, body and soul, and it's our responsibility to help enable access for all people, regardless of race, gender, beliefs, background or ability. We strive for inclusion at Stio and in our local and national communities.

YOUR ROLE

The Data Analyst is a key early member of Stio's Data & Analytics team, working alongside the Director of Data & Analytics to expand how the business uses data to make decisions. This is a full-stack, horizontal role: the work spans data infrastructure (ingestion, modeling, transformation) through analysis, BI development, and direct stakeholder partnership across Finance, Merchandising, Marketing, Operations, Inventory Planning, and B2B. You'll work where the highest-leverage problems are and grow the breadth and depth of the analytics function in the process.

You'll work in a stack built around Snowflake, Fivetran, dbt, Power BI, GitHub, and increasingly Python in addition to SQL and R. AI-assisted development is the default form factor for the team. Most of the code we ship is written collaboratively with AI agents in tools like Claude Code, then reviewed, tested, and iterated. The expectation is not that you arrive an expert in AI tooling. The expectation is that you bring strong fundamentals - the kind of data and modeling intuition that lets you catch silently wrong AI output that runs cleanly and passes tests - and that you're genuinely curious about how this part of the craft is evolving. As an early team member, you'll help shape how we work in this environment, not just execute someone else's playbook.

We're looking for an analyst who connects what they see in the data to the bigger picture and who has a strong bias for tying analysis to action. The right person doesn't hesitate to sweep the floor (fix a broken Excel link), isn't afraid to question the status quo (does this metric actually measure what it claims to?), and would rather quickly solve a pressing business problem with simple analysis than build a sophisticated model that collects dust. A foundation of technical skills is essential. Even more important is an eagerness to learn new things, sound judgment under ambiguity, and a desire to drive positive progress at Stio.

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 Development, Marketing, DTC, B2B, Finance, Operations, Inventory Planning) to translate ambiguous questions into well-defined analyses, dashboards, and data products. You'll own these end-to-end: scoping, building, validating, and communicating findings.
  • Build and maintain dbt models that turn raw source-system data into trustworthy, well-documented datasets. Write the tests and documentation that let both humans and AI agents downstream rely on the work.
  • Develop and maintain the semantic context, dashboards, and reports that the rest of the business uses to operate day-to-day.
  • Own metric definitions and business semantics. Drive alignment when stakeholders disagree on what a definition or number means.
  • Review and harden AI-generated SQL, dbt models, and Python code with the judgment to catch issues that pass tests but are semantically wrong. The majority of your output will be code you've collaborated on with AI agents, and you'll bring the data intuition that makes that work trustworthy.
  • Investigate ambiguous data questions where the answer isn't in the schema: talk to source-system owners, investigate edge cases, reconcile conflicting definitions, and improve our model of the business.
  • Help build and maintain Stio's data infrastructure - currently Snowflake, Fivetran, dbt, GitHub, Power BI, R, and Python - and contribute to decisions about where the stack should evolve.
  • Improve data governance for both the Data & Analytics team and the business at large by creating documentation that's actually useful and that AI agents can consume as context for future work.
  • Continuously develop your skills as the practice of data analytics evolves. This is a real part of the job, not something done on the side.

YOUR SKILLS AND EXPERIENCE

  • 3+ years of professional experience as a data analyst, analytics engineer, or similar role
  • Advanced SQL: CTEs, window functions, comfortable wrangling messy real-world data, can read and reason about query plans well enough to know when something is off
  • Hands-on experience with dbt, including writing models, tests, and documentation. You don't need to have built a dbt project from scratch, but you should be comfortable contributing to one and know what good looks like
  • Experience with cloud data warehouses (Snowflake, BigQuery, Databricks, Redshift, Microsoft Fabric, or similar)
  • Version control with Git/GitHub as part of your normal workflow
  • Experience as a developer with at least one BI tool (Power BI, Tableau, Looker, Omni, or similar)
  • A real point of view on AI-assisted development for analytics work - what it's actually good at, where it falls down, what you do to make the output trustworthy
  • History of building collaborative, trusting relationships with non-technical stakeholders
  • Comfort presenting findings to leadership verbally, in writing, and visually

PREFERRED ADDITIONAL SKILLS AND EXPERIENCE

Though not required, we would consider the following as an added plus:

  • Working knowledge of Python and/or R for analysis
  • Experience with the components of our data stack (Snowflake, Fivetran, dbt, GitHub, Power BI, Python, R, Claude Code, Codex)
  • Experience with some of the systems we use: NetSuite, Shopify, Google Analytics, Segment, Klaviyo
  • Professional experience at a DTC or omni-channel retail, apparel, footwear, or outdoor company
  • Experience working in a small or solo data team where you owned the work end-to-end

THE FINE PRINT

  • Must be able to work in a stationary position 50% - 75% of the work day
  • Medical, Dental Vision plans
  • Company Paid Long Term Disability
  • Employee Assistance Programs
  • 401k with Match
  • Generous paid time off policies
  • Gear test, perks and more

We provide competitive compensation packages, inclusive of base pay, incentives and benefits. The base salary range for this role is $85,000-$100,000. It would not be typical for someone to be hired at the top end of the range for the role, as actual pay will be determined based on several factors including experience, skills, and qualifications.

This job description is not necessarily an exhaustive list of all responsibilities, skills, duties, requirements, efforts, or working conditions associated with the job. While this is intended to be an accurate reflection of the current job, we reserve the right to revise the job or to require that other or different tasks be performed. Stio is an equal opportunity employer of all qualified individuals, including minorities, BIPOC, LGBTQ+, veterans & individuals with disabilities.