Lead Analytics Engineer in London

About MUBI

MUBI is a global streaming service, production company and film distributor dedicated to elevating great cinema. To make this possible, we create, curate, acquire and champion visionary films, bringing them to audiences all over the world. We have a team of brilliant, dedicated and passionate people to help bring our mission to life. From London to New York, Istanbul to Paris, and Berlin to Mexico - we work together to realize MUBI’s vision. That’s where you come in! Join our global team and help us make great cinema accessible to everyone, everywhere.

About the Role

We're looking for a Lead Analytics Engineer to own the data layer that powers analytics, data science, and self-serve reporting at MUBI. This is a hands-on, senior individual contributor role reporting to our Head of Data. You'll set the technical bar for the discipline: owning our core data models, evolving the semantic layer that lets teams answer their own questions in Omni, and making trusted, self-serve data the default across the company. You'll partner directly with data scientists, engineers, and business stakeholders to turn ambiguous questions into well-governed data products and dashboards that drive real decisions.

Leadership here is technical, not managerial. You'll raise the bar through the standards you set, the code you review, and the people you level up - but this role has no direct reports. Because data directly shapes how we acquire, retain, and delight film lovers, this role has real commercial reach - influencing decisions across product, marketing, finance, personalisation, and content.

We work hybrid-remote where we require 3 office days in London. Our core days are Tuesday, Wednesday & Thursday, with the flexibility to use our offices on the remaining two days if you wish.

Where you’ll have impact:

• Own the dbt modelling layer. Design and build our core, mission-critical models and the standards, tests, and documentation that keep them reliable and performant as we scale.
• Treat data as a product. Evolve our models and semantic layer so teams across product, marketing, content, and finance can reliably self-serve from high-quality, well-governed data.
• Set the technical direction. Establish and champion best practices for analytical pipelines: review code, define the patterns others adopt, and raise the data-quality bar across the team.
• Partner with stakeholders. Work directly with teams across the business to understand what they need from data and translate that into well-designed data products and dashboards that drive decisions.
• Put AI to work across the modelling lifecycle. Use AI tools and agents to accelerate dbt development and improve data quality, and help the team do the same.

What you’ll bring:

• 5+ years of experience in an analytics engineering or data engineering role and a track record of owning an analytics / modelling layer end-to-end, not just contributing to one.
• Hands-on dbt expertise and strong SQL, comfortable working with large, complex data sets. This is core to the role.
• A track record of enabling self-serve analytics - building data products that let stakeholders answer their own questions.
• Commercial sharpness - you understand what the business needs from its data and you’ll design trustworthy data products around it.
• Strong communication and stakeholder management skills, working across technical and non-technical teams.
• Detail-oriented and pragmatic, with a 'no task too small' attitude.
• Familiarity with Snowflake, AWS, and modern BI tools (we use Omni).

Nice to have:

• Experience in a fast-paced, high-growth environment (e.g. startup or scale-up).
• Experience leading or contributing to cross-functional projects with teams such as Product, Marketing, Finance, or Engineering.
• Genuine interest in film and in MUBI's mission.

MUBI is committed to being an Equal Opportunity Employer. That means it's our responsibility to ensure that all candidates are not discriminated against in our hiring processes and our employment decisions based on their race, color, religion, nationality or ethnic origin, age, gender identity or expression, sex, marital status, physical or mental disability, socioeconomic background, sexual orientation, family or parental status, or any other applicable characteristic.