Analytics Engineering Advocate - Europe

Lightdash
RemotePosted 27 March 2026

Tech Stack

Job Description

Analytics Engineering Advocate - Europe ABOUT LIGHTDASH Lightdash is an open source BI tool that instantly turns your dbt project into a full-stack BI platform. We’re building the best BI tool for analytics engineers by letting them manage everything as code, from the comfort of their text editor and command line. Once the data team has written the metrics, then Lightdash enables self-serve for the entire business, so your data is accessible for the whole team. We’re helping data teams build data-driven companies so they can make better decisions, faster. HOW WE WORK AT LIGHTDASH - We build in public, by default. We’re an open source product, so having shared context is important so that people can contribute to Lightdash. As a team, we also think that we make the best decisions when everyone has a lot of the same information. We don't oversell and under-deliver: we want the experience of using Lightdash to be as awesome as the experience we're selling. - We challenge problems, not people. We ask ourselves “why is this broken?” not “who is breaking this?” - We’re highly collaborative. We’re a group of people that are happy working independently, but love being part of a team. ****We not only work on problems as a team, but we also listen to the feedback from our community and our users. We invest in tools and processes that allow us to do this, even while fully remote. - We bias towards impact. We’d rather build something to 80% and get it in front of users so we can iterate on fast feedback than build something to 100% just to find out it’s not the right thing. We spend a lot of time thinking about how our work solves real user problems. We work on the highest impact problems even if they’re something a bit “out of your remit”. ABOUT THE ROLE At Lightdash, we're obsessed with the success of our users. Our fast, empathetic, and deeply technical support is one of our superpowers. We help teams with everything from building dashboards and writing SQL to analytics engineering best practices and data modeling strategy. If you have a passion for helping teams win with data, and the technical skills to debug their toughest problems, we're looking for an Analytics Engineering Advocate to join the Lightdash team. Our users' experience of Lightdash goes beyond product features. It includes every touchpoint and interaction they have with our community and team. In this role, you'll be the voice for our community, combining technical expertise with relationship-building to help users succeed with Lightdash and modern analytics engineering. You'll spend a significant portion of your time directly helping users in Slack and on calls — diagnosing issues, answering questions, and pair-programming through problems. A note on AI: We're investing heavily in AI-powered workflows throughout Lightdash, and we expect this role to be at the forefront of that evolution. You'll use AI tools daily—for task management, technical problem-solving, analytics engineering work, and potentially contributing to our codebase. The ideal candidate is excited about the rapid pace of AI development and eager to incorporate new capabilities into their work and share that knowledge with our community. AREAS OF RESPONSIBILITY Obsess over user success through technical problem-solving Our users' wins are our wins. You'll be active daily in shared customer Slack channels, responding to user questions, triaging bugs, and jumping on calls to pair-program through complex issues. You'll balance fast, practical solutions with thoughtful, strategic guidance on analytics architecture and process improvement. You'll leverage AI tools to work more efficiently and help users understand how to do the same. Be the Lightdash expert You'll be the go-to Lightdash pro, both internally and in the community. You'll stay current with our latest features, including our evolving AI capabilities (using Lightdash for our own analytics and demos), understand how they fit into ... (truncated, view full listing at source)
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