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BeReal

Head of Data - BeReal

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Summary

Lead BeReal’s data team to build analytics infrastructure, run A/B tests, and drive product decisions using GCP, BigQuery, and Amplitude.

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.

  • Build the team. Lead, mentor and hire across Data Engineering, Analytics Engineering and Data Analytics. Establish clear ownership, develop the people in the team and raise the technical and analytical bar.

Our Data Stack

  • Infrastructure: Google Cloud Platform, BigQuery, Spanner.

  • Orchestration & transformation: Airflow, dbt.

  • Product analytics: Amplitude.

  • Visualisation & analytics: Hex, Tableau, internal tools.

This is our current stack, not a constraint. You will have significant latitude to simplify, rationalise and evolve it when there is a strong reason to do so.

Profile

  • 8+ years in data, with deep roots in Data or Analytics Engineering, or data architecture.

  • A hands-on builder: you’ve designed, built and run modern data platforms, ideally from scratch, and know how architecture evolves with scale.

  • Strong across the stack (warehousing, ingestion, orchestration, transformation, modeling, observability), with strong SQL and enough depth to challenge production pipelines and models.

  • Deep data quality expertise: testing, monitoring, lineage, ownership and source-of-truth design.

  • Experience with high-volume, user-level data and with building self-service analytics for non-data teams.

  • Solid in experimentation and A/B testing. Mobile experience is a plus.

  • Hands-on with AI in data workflows (LLMs, agents, natural-language analytics), and a clear view of where it really adds value.

  • Strong stakeholder management and business judgment: you turn vague needs from Product, Growth, Engineering and leadership into clear metrics and a roadmap.

  • You’ve led data people or are ready to own a multidisciplinary team. This can be your first Head of Data role.

  • You ship fast, favour ownership and pragmatism over process, and explain complex topics clearly to anyone, founders included.

  • English is our working language. French is a plus.

Experience with Data Science or production Machine Learning is valuable but not a prerequisite for the role.

Benefits

  • Competitive salary based on experience.

  • Swile lunch vouchers.

  • Gymlib, 100% covered by Voodoo.

  • Premium SideCare healthcare coverage for you and your family, 100% covered by Voodoo.

  • Wellness activities in our Paris office.

Skills

Apply

See also