Analytics Engineering Advocate - Europe

Analytics Engineering Advocate - Europe

Full-Time 60000 - 80000 £ / year (est.) Remote
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At a Glance

  • Tasks: Support users with analytics engineering, troubleshoot issues, and create engaging tutorials.
  • Company: Join Lightdash, an innovative open-source BI tool transforming data accessibility.
  • Benefits: Flexible remote work, competitive salary, and opportunities for professional growth.
  • Other info: Diverse and inclusive team committed to your career development.
  • Why this job: Be the voice of our community and help teams succeed with data-driven decisions.
  • Qualifications: Experience with dbt, SQL, and a passion for teaching and community engagement.

The predicted salary is between 60000 - 80000 £ per year.

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 broader BI and analytics engineering workflows, and share this knowledge widely. You'll represent Lightdash at community events, conferences, and meetups with curiosity and enthusiasm, showcasing how AI is transforming analytics workflows.
  • Teach and share: Create and deliver world-class tutorials and demos for Lightdash and examples of analytics engineering best practices. Whether through docs, guides, blog posts, video tutorials, or code examples, you'll make complex concepts accessible and help users level up their skills. You'll use AI tools to accelerate content creation while maintaining quality and authenticity.
  • Build and grow community: Develop and execute strategies to grow and engage the analytics engineering community around Lightdash. This includes cultivating relationships with community members, identifying product champions, and creating spaces for knowledge sharing and collaboration around modern analytics practices.

What we're looking for

  • Technical expertise: Strong hands-on experience with dbt, SQL, data modeling, and modern data stacks. Comfortable with git, the command line, and data visualization tools. Proficient with AI coding assistants and productivity tools; you should be comfortable using AI to write code, debug issues, and accelerate your work. Resilience when facing ambiguous or complex debugging challenges.
  • Industry knowledge and product vision: Deep understanding of business intelligence and analytics engineering workflows. Ability to connect user needs to product strategy and feature development. Excitement about how AI is transforming the analytics landscape and eagerness to stay current as the space evolves rapidly.
  • Communication and relationship building: Exceptional written and oral communication skills—you can explain technical concepts clearly to varied audiences. Natural teacher who can train people through live calls, in-person, videos, documentation, etc. Strong empathy, curiosity, and active listening skills; you genuinely care about understanding users' contexts and constraints. Relationship-builder who enjoys connecting with community members.
  • Logistics: Able to work UTC +/- 3.

💜 We believe that to build a product that works for a diverse group of people, we need a diverse team. So, we strongly encourage candidates of all different perspectives, experiences, backgrounds and identities to apply. We’re committed to hiring people regardless of race, religion, colour, national origin, sex, sexual orientation, gender identity, age or disability. And once you join us, we’re committed to building an inclusive, supportive place for you to do the best work of your career.

Analytics Engineering Advocate - Europe employer: Lightdash

At Lightdash, we pride ourselves on being an excellent employer that fosters a vibrant and inclusive work culture. As a Marketing Associate, you'll enjoy real ownership of your projects, direct mentorship from experienced professionals, and the opportunity to grow within a fast-paced startup environment. With competitive salaries and a focus on employee development, we empower our team members to make meaningful contributions while nurturing their careers in the exciting world of data analytics.

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Contact Details:

Lightdash Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Analytics Engineering Advocate - Europe

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Lightdash!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Analytics Engineering Advocate - Europe at Lightdash.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Lightdash.

✨Apply Directly through Our Website

When you find a suitable opening like Analytics Engineering Advocate - Europe at Lightdash, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Analytics Engineering Advocate - Europe

dbt
SQL
Data Modelling
Modern Data Stacks
Git
Command Line
Data Visualisation Tools

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Lightdash, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Lightdash. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Lightdash

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Lightdash!

✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.