About Voodoo

Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 1,000 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta.

Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz.

Team

At BeReal, we are dedicated to authenticity in social media. By encouraging users to share unfiltered moments, we foster genuine connections and celebrate real life.

We are now an international team of 100+ people with 40M+ monthly active users. Backed by Voodoo, our team is fully focused on scaling BeReal into an iconic social network used by hundreds of millions.

Data is becoming increasingly central to how we build the product, understand our users and make decisions. We are looking for a Head of Data to own the function end to end and build the foundations required for the next stage of BeReal's growth.

Role

You will lead a team of Data Engineers, Analytics Engineers and Data Analysts, reporting to the CEO and partnering closely with Product, Growth, Engineering and leadership.

This is a hands-on leadership role. BeReal deliberately operates with small, strong teams, and we are looking for someone who can define the direction while still going deep technically: reviewing architecture and data models, investigating quality issues, challenging pipelines, writing queries and building when necessary.

You should be the kind of leader who could design a modern data platform from scratch, scale it as the company grows, and make sure the people using it can trust what comes out of it.

What you'll own

Build and evolve the data platform. Own BeReal's data architecture end to end: ingestion, storage, orchestration, transformation, modeling, observability and access. Build a platform that is simple, scalable, reliable and cost-efficient as both traffic and the number of data consumers grow.

Make data trustworthy. Raise the standard of data quality across the company through clear sources of truth, ownership, testing, monitoring, lineage and consistent metric definitions. Identify inconsistencies proactively and build systems that prevent them from recurring.

Data modeling and foundations. Define how our core entities, events and business concepts are represented across the warehouse. Build models that are reliable, understandable and maintainable as the product evolves.

Decisions, not dashboards. Turn large, complex user-level datasets into clear insights and recommendations that Product, Growth and leadership can act on. Help teams distinguish meaningful signals from noise and focus on the questions that matter.

Product analytics and experimentation. Own the methodology around instrumentation, Amplitude usage, event tracking, metric design and A/B testing. Ensure experiments are designed and interpreted rigorously and that product decisions are grounded in reliable data.

Make data self-service. Give Product, Growth, Engineering and leadership the tools and models they need to answer most questions independently, without creating a dependency on the Data team for every request.

AI-powered data access. Build or integrate practical ways for employees to interact with company data through AI (agents, bots, natural-language analytics and automated workflows) while maintaining strong standards around accuracy, permissions and governance.

Stakeholder management and prioritisation. Serve as the primary data partner to C-level executives and teams across Product, Growth and Engineering. Understand their needs, challenge requests when necessary, arbitrate between competing priorities and translate them into a coherent, high-impact data roadmap.

Technical leadership. Set strong engineering and analytics standards across the function. Review architecture, pipelines, models and queries, challenge technical choices and remain close enough to the work to intervene directly when needed.