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Data Analytics Engineer

SumUp LogoSumUp
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Salary

$100,000 - $120,000

Location

Boulder, CO

Posted

Yesterday

The US Analytics team is building the data foundations that power SumUp's US operations. We design reliable data models, keep our infrastructure clean, and turn complex datasets into insights the business can act on. You'll join at a point where there's real work to own — from shaping how data is structured to improving the tools and dashboards that teams rely on every day. If you're someone who's been close to data in an analytical role and is ready to go deeper into how it's built and maintained, this is a meaningful next step.

What you'll do

  • Build, maintain, and document DBT models in a Snowflake environment, keeping data clean, reliable, and well-structured
  • Develop and maintain Tableau dashboards and data sources that stakeholders across the business trust and use independently
  • Rotate through day-to-day data operations support — handling ad hoc requests, troubleshooting reporting issues, and diagnosing pipeline problems
  • Contribute to modernizing our data infrastructure, helping business stakeholders self-serve through AI-assisted tooling
  • Own stakeholder relationships independently — gathering requirements, setting clear expectations, and communicating confidently with technical and non-technical audiences alike

You'll be great for this role if…

  • Strong experience building or structuring datasets — not just querying them based on others work
  • Solid SQL and DBT Core skills, hands-on experience with Snowflake and
  • Proven ability to build Tableau dashboards that stakeholders genuinely rely on
  • Strong communicator who can own stakeholder conversations, gather requirements, manage expectations, and push back when a request isn't clearly defined
  • High attention to data quality and the confidence to work through problems independently before escalating
  • Familiarity with AI-assisted data tools such as GitHub Copilot or Cursor
  • Familiarity with Salesforce

Bonus points for

  • Advanced DBT experience
  • Experience with self-serve or semantic data layers
  • Contributions to an AI agent knowledge base or prompt engineering work
  • Understanding of the limitations of LLMs when applied to data problems
  • Previous experience in a fast paced, team environment

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