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Data Analyst

Job in Denver, Denver County, Colorado, 80285, USA
Listing for: UnionHub
Full Time, Part Time position
Listed on 2026-02-07
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager
Salary/Wage Range or Industry Benchmark: 85000 - 105000 USD Yearly USD 85000.00 105000.00 YEAR
Job Description & How to Apply Below
Position: Data Analyst - Payments

Location: Hybrid (Denver Metro Area) – In-office at least 1 day per week (RiNo neighborhood)

Job Type: Full-Time

Pay range: $85K-$105K per year

Union Hub is a fast-growing SaaS company delivering cutting-edge insurance management solutions. We’re on a mission to simplify complex workflows and improve outcomes through intuitive, well-crafted technology. As a Data Analyst
, you’ll play a critical role in shaping our data strategy, ensuring accuracy and accessibility, and empowering teams to make smarter decisions. You’ll work with stakeholders across the organization to design scalable reporting solutions, provide actionable insights, and help optimize performance.

Our Core Values

Simplicity | Security | Innovation | Accessibility | People-Centric Culture

Role Overview

We’re looking for a Data Analyst with strong technical skills in SQL and relational databases, and a solid background in data automation and data quality management
, as well as payments/billing reconciliation
. This role will design and maintain reliable data pipelines, ensure data cleanliness across multiple systems, and prepare structured and unstructured datasets for downstream analytics and Large Language Model (LLM) applications. You will also support accounting and billing workflows, including payments reconciliation and spreadsheet-based financial analyses.

Key Responsibilities & Technical Skills
  • Payments/billing reconciliation
  • Accounting and finance-related spreadsheet analysis
  • Data quality monitoring and validation
  • Data modeling and schema design
  • Processing of unstructured data
Required Qualifications
  • Strong proficiency in SQL and relational databases.
  • Proficiency with Excel and spreadsheet-based data analysis.
  • Experience with Payments/Billing Reconciliation
  • Familiarity with C#/.NET frameworks.
  • Experience with data visualization tools (Power BI, Tableau, Looker).
  • Strong analytical and problem-solving skills with excellent attention to detail.
  • Ability to work collaboratively in a fast-paced, cross-functional environment.
  • Strong communication skills, with the ability to present insights to both technical and non-technical audiences.
  • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or related field; equivalent experience; or completion of a recognized analytics bootcamp.
Preferred Qualifications
  • Experience in Insurance, Benefits, Payments, Banking, SaaS, or Fintech environments.
  • Experience with APIs
    , large datasets, and cloud-based data warehousing (Azure Synapse, Snowflake, Big Query).
  • Experience working on an agile team.
  • Background with Azure environments.
Bonus Skills
  • ETL pipeline design, development, and maintenance
  • Data automation and import/export workflows
  • Python (Pandas) / R for data manipulation, analysis and automation
  • LLM-focused data preparation
  • Workflow orchestration (Airflow, Prefect)
Why Join Us?
  • Be part of a collaborative, thoughtful, and curious team.
  • Enjoy a hybrid work model with purposeful in-office days for connection and collaboration.
  • Competitive salary, 401(k) match, and annual discretionary bonus eligibility (typically up to 10% of base salary; not guaranteed).
  • Comprehensive benefits package including medical, dental, vision, life, and LTD coverage, employer-paid supplemental insurance, technology allowance, parental leave, and more.
  • Room to grow within a scaling product organization.
  • All interested candidates must apply through this platform. The position is currently open and accepting new applications.
  • Applications will be reviewed on a rolling basis, and the role will remain open until filled. Early submissions are highly encouraged.
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