Make is the platform to manage all your automations and AI agents in one visual landscape – for teams driving business impact without relying on developers. Part of Celonis, a global leader in process intelligence recognized on the Forbes Cloud 100 for seven consecutive years, we're headquartered in Prague, Czechia, with hubs in Madrid, Munich, Raleigh, and Pristina, and teams across the UK, France, India, and the Netherlands, among other locations.
At Make, we’re moving away from manual dashboards and repetitive ad-hoc data requests toward AI-powered self-service analytics, where anyone in the company can ask a question and get a trusted answer on their own. We’re looking for an Analytics Engineer to help lead that shift.
This isn’t a pure backend role. You’ll sit between data engineering, analytics and the business. You’ll build the models and context that make data reliable, and the AI tools that make it accessible.
Why this role
- Company-wide impact. Your work will change how teams across Make make decisions, not just how one team reports.
- AI at the core, not on the side. You’ll work with Claude every day and build AI assistants and agent workflows that help colleagues answer questions on their own.
- Strong foundations, room to lead. Our core pipelines are built and documented, so you won’t start from zero. You’ll own key areas and shape what comes next.
- Close to the business. You’ll work directly with commercial teams on revenue, retention, sales performance and marketing effectiveness.
What you’ll do
- Build and maintain reusable data models, transformations and pipelines that turn source data into trusted datasets for analytics and operational use
- Define and maintain shared metrics, business rules and documentation, so core metrics stay accurate and people and AI agents interpret data the same way
- Build AI assistants that let colleagues explore data independently, and test that their answers are accurate
- Create reusable agent skills and workflows that automate tasks like development, analysis, validation and documentation, with human review where needed
- Partner with stakeholders: understand the real problem, challenge the request when needed, and ship the simplest solution that works
- Experiment with new AI approaches and share what you learn, inside the team and beyond
What you’ll bring
- Relevant experience. Ideally 3–5 years in analytics engineering, data engineering or data analytics.
- Commercial curiosity. You want to understand how a business works, and you care more about measurable impact than elegant engineering.
- Clear communication. You can explain a technical project to a non-technical colleague without jargon.
- AI-native habits. You use AI tools daily and know how to give them context, break work down and verify the output.
- Strong SQL. You have experience building, optimising and maintaining complex analytical transformations.
- Cloud data warehouse experience. You’ve worked hands-on with a modern cloud data warehouse and understand how modelling and query design affect performance and cost.
- Engineering practices for data. You’re familiar with version control, code review, automated testing and controlled deployment of changes.
- Python and data modelling. You use Python for automation and data processing, and you have a practical understanding of data modelling and pipelines.
- Ownership and a get-it-done attitude. You take initiative, thrive with autonomy, and bring positive energy to the people around you.
Nice to have
- Experience as an Analytics Engineer or Data Engineer, or as a Data Analyst with hands-on pipeline experience
- Familiarity with SaaS/B2B metrics such as ARR, churn, retention and conversion
- Experience with semantic layers, structured company context for AI, or reusable agent workflows
What matters most
Years of experience alone don’t determine success here. We care most about what you can build, how you think and the impact you deliver.
What we offer:
- 📝 RSUs grant in a rapidly growing company raising its value every day
- 💸 Annual bonus
- 🌎 Multinational team with 42 nationalities creating the future of automation
- 🎓 Learning & Development plan (online language, professional courses, conference tickets and other trainings) & 2 Company Learning Days per year
- 🌳 1 Company Impact Day per year
- 🍎 Notebook/Macbook
- 🏝 25 days of vacation
- 🫶 10 care days to care for your loved ones
- 👨👩👧👦 Extra parental vacation (3-6 months)
- 👶 RSUs grant for a newborn child
- ☂️ Life insurance
- 🏋️ Gympass
- 💳 Meal and transportation tickets, medical insurance
- 🥳 Team buildings, parties, and company events multiple times a year
- 🏡 Flexible working hours + home office
If you see a match, let us know and apply now!
#LI-DP2
What we stand for:
🤝 We roll together - We practice radical candor, challenge ideas openly, and use feedback to get better together.
🚀 Customer impact first - We get things done with craftsmanship, focus on outcomes, raise the bar, and create real customer impact.
⚽ Game on! - We take extreme ownership, move fast, and embrace change as opportunity.
For more, feel free to check out our Life at Make Instagram, Meet-up page, or YouTube to get a sense of the vibe.
At Make, we know that exceptional work comes from people who bring different perspectives and experiences. We build a place where everyone feels welcome, heard, and empowered to create, contribute, grow and make an impact. We encourage people of all backgrounds, identities, abilities, and experiences to apply. Our hiring decisions are based on your qualifications, skills, merit, and the needs of our business. We have zero tolerance for discrimination or harassment of any kind.
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