Staff Product Analytics Engineer - BeReal

Voodoo

About The Position

Data is at the core of every decision we make at BeReal. As a Staff Product Analytics Engineer, you will own BeReal’s product analytics layer end-to-end. You will act as the most senior technical voice on analytics, reporting directly to the VP Engineering. Working at the intersection of data engineering, analytics, and product, you will partner closely with Product Managers, Engineers, and Data stakeholders to build a scalable, reliable, and self-service analytics foundation that empowers better product decisions. Highly autonomous and hands-on, you will define the roadmap, architect robust data models, and build the tools and infrastructure that make data accessible and actionable across the organization.

Requirements

Expertise in analytics engineering, data engineering, or product analytics.
Deep expertise in SQL, dbt, and BigQuery.
Strong proficiency with product analytics tools such as Amplitude.
Experience building scalable data models and self-service analytics layers.
Comfortable with Python and/or Go.
Strong product sense and ability to partner effectively with Product Managers.
Hands-on, autonomous, and results-oriented mindset.
Ability to balance technical excellence with business impact.
Excellent communication skills and ability to influence cross-functional teams.
Fluent in English.

Nice To Haves

French is a plus.

Responsibilities

Define and execute BeReal’s product analytics roadmap, aligning modeling, observability, and tooling with product priorities.
Partner closely with Product Managers to translate product loops, retention mechanics, and experimentation needs into scalable data models.
Build and deploy AI-powered internal analytics tools that enable stakeholders to query data in natural language.
Own the integration between BigQuery, Amplitude, and our experimentation framework to ensure a single source of truth for metrics.
Design and maintain a self-service metrics layer that enables PMs to independently analyze funnels and experiments.
Write production-grade dbt models and optimize SQL transformations for reliability, performance, and scalability.
Lead technical reviews and establish best practices for analytics engineering.
Collaborate with Backend and Mobile teams to ensure analytics instrumentation is robust and analytics-ready from day one.
Monitor data quality and observability to guarantee trust in product metrics and reporting.