Analytics Engineer - All Genders

Role overview

Shape the analytics layer that teams use to make product and business decisions. You’ll turn raw product data into dependable, well-documented datasets and metrics for reporting, experimentation and product improvement, working with teams across the organization. The role combines hands-on modeling with helping colleagues interpret results and answer questions independently.

Responsibilities - Build and maintain scalable analytics models using dbt or a comparable transformation framework. - Transform raw product data into business-ready datasets, with validation, tests and documentation. - Define and maintain shared metrics so teams can use consistent measures in their decisions. - Partner with product and growth colleagues on measurement plans, experiments, funnels, retention and customer insights. - Develop reporting and self-service analytics using tools such as Power BI, Hex or internal AI tools, and help stakeholders use them. - Apply AI coding tools to modeling, testing and documentation, and support wider adoption of AI for data work.

Requirements - Strong practical experience building analytics models with dbt or a similar tool, plus a sound understanding of dimensional modeling. - Advanced SQL skills and experience with large analytical datasets. - Experience with a cloud data warehouse such as Amazon Redshift. - Experience creating dashboards or self-service reporting in Power BI or a comparable BI tool. - Familiarity with product analytics and experimentation methods. - Hands-on use of AI assistants and coding tools; experience configuring MCPs and helping a team adopt AI is requested. - Ability to explain technical findings clearly and turn analysis into useful recommendations. - Must be based in the advertised country and authorized to work there; sponsorship and relocation support are unavailable.

Nice to have - Experience with semantic layers or self-service analytics platforms. - Python skills for data processing and automation, such as using pandas. - Familiarity with workflow orchestration tools such as Airflow.