Analytics Engineer

Job Description: Own the data models that scale our portfolio and turn messy questions into high-stakes decisions. Work closely with product, monetisation, UA, and finance leads to turn ambiguous questions into clear models and reliable metrics. Design and maintain the dbt project on BigQuery - dimensional models, incremental loads, reusable macros, thorough tests, and documentation that actually gets read. Build and iterate on Metabase dashboards that give non-technical teams the confidence to make decisions without pinging you for every question. Monitor production dbt runs, triage failures, trace issues from the dashboard layer all the way back to raw sources, and communicate impact and resolution to stakeholders. Requirements: 5+ years of hands-on analytics engineering or a senior analyst role with heavy SQL and modelling work. Strong SQL fluency and real experience with a cloud data warehouse (BigQuery preferred; Snowflake or Redshift also fine). 2+ years of production dbt experience: you've built and maintained dimensional models, written incremental models, authored macros, and set up tests that catch real problems. Track record of building dashboards for non-technical stakeholders - people who judge your work by whether it helps them make better decisions, not by how clever the SQL is. Genuine curiosity about the data you work with. Ability to ramp up fast on unfamiliar business domains. Clear, concise communicator. Benefits: Equal opportunities for everyone Diversity and inclusion initiatives