The posting
Build analytics people can trust. Help define what analytics looks like in an AI-first world.
Why this role matters
What you’ll own
- Understand the problem before committing to a solution.
- Help shape priorities, not just implement them.
- Build across the stack wherever the problem takes you.
- Ship incrementally and learn from real usage.
- Measure outcomes and iterate.
- Use AI throughout your workflow.
- Diagnosing and solving complex problems across a large, mature codebase.
- Strengthening the security, performance, scalability, reliability and resilience of Matomo.
- Protecting the integrity, accuracy and trustworthiness of the data customers rely on.
- Strengthen capabilities that support increasingly demanding enterprise use cases.
- Building and evolving APIs and platform capabilities used by Matomo plugins and integrations.
- Evolving how Matomo handles consent, privacy and responsible data collection.
- Advancing server-side tracking, data anonymisation and data-health monitoring.
- Enhancing analytics capabilities such as goals, ecommerce reporting and dashboards.
- Simplifying complex analytics workflows and making powerful functionality easier to use.
- Evolving Matomo's design system to create a more consistent and usable product experience.
How we work
- Customer problems over technical elegance.
- Shipping over endless planning.
- Simple solutions over unnecessary complexity.
- Ownership over handoffs.
- Iteration over perfection.
- Clear writing over excessive meetings.
- Pragmatic engineering over abstract architecture.
- AI where it helps us move faster.
- Measuring outcomes over assuming we were right.
What we’re looking for
- What problem are we solving?
- Who has this problem?
- Is this the simplest useful solution?
- How will we know this made things better?
- What should we do if the data shows we were wrong?
You’ll probably thrive here if
- You prefer owning outcomes over receiving detailed tickets.
- You enjoy solving difficult problems in existing systems as well as building new functionality.
- You can quickly diagnose complex or intermittent bugs.
- You can move from customer feedback or operational evidence to investigation, product decision and implementation.
- You care about reliability, performance and data accuracy, not only visible feature work.
- You can improve a mature codebase without assuming it needs to be rewritten.
- You use AI tools heavily and are actively improving how you work with them.
- You are pragmatic: you can make a focused improvement now while recognising when a deeper change is needed.
- You can explain technical and product trade-offs clearly.
- You enjoy working across product, engineering, UX, data and customer feedback.
- You like small teams where your decisions and output visibly matter.
- You're excited to take on increasingly ambiguous problems.
- You want to grow beyond implementation into shaping products and technical decisions.
You may not enjoy this role if
- You mainly want to work on new greenfield products.
- You see maintenance, debugging, reliability or performance work as less valuable than feature development.
- You want a product manager to define most requirements before you start.
- You are uncomfortable investigating problems where the cause is initially unclear.
- You prefer replacing existing systems rather than understanding why they work as they do.
- You measure success mainly by code quality rather than user or business impact.
- You are uncomfortable using AI as part of your normal engineering workflow.
- You need a large team, narrow responsibilities, or highly formal processes to be effective.
- You prefer polishing a solution extensively before showing it to users.
- You dislike writing proposals, documentation, or product notes.
- You are uncomfortable balancing speed, backwards compatibility and long-term platform health.
