Analytics Engineer

BlueThrone is seeking an Analytics Engineer to define how the business measures success. You'll partner with product, monetisation, UA, and finance teams to transform ambiguous questions into reliable metrics and trustworthy KPIs that drive mobile app performance decisions.

• Stakeholder Partnership: Translate business questions from product, finance, UA, and monetisation teams into precise analytical requirements.
• Data Modelling: Design and maintain dimensional models (fact/dim) on BigQuery using dbt, including incremental loads, macros, tests, and documentation.
• Dashboards & Self-Serve Analytics: Build and iterate on Metabase dashboards enabling non-technical teams to make data-driven decisions independently.
• Data Analysis: Investigate anomalies, run ad-hoc analyses, and surface insights such as Week-2 retention trends, cohort profitability, campaign scalability, and pricing experiment impacts.
• Data Quality & Reliability: Monitor dbt production runs, triage failures, trace issues across the stack, and communicate impact to stakeholders.
• Mobile Metrics Expertise: Own core mobile KPIs—DAU/MAU, LTV, retention cohorts, ARPU, ROAS—ensuring accuracy and trustworthiness.
• Process Improvement: Identify gaps in the data stack and propose practical solutions.

Must-haves:

• 5+ years of hands-on analytics engineering or senior analyst role with heavy SQL and modelling work.
• Strong SQL fluency and production experience with a cloud data warehouse (BigQuery preferred; Snowflake or Redshift acceptable).
• 2+ years of production dbt experience including dimensional models, incremental models, macros, and testing.
• Track record of building dashboards for non-technical stakeholders.
• Genuine curiosity about data and ability to ramp up quickly on unfamiliar business domains.
• Clear and concise communication skills.

Nice-to-haves:

• Experience in gaming, mobile apps, or high-volume event-driven data environments.
• Familiarity with Metabase.
• Event tracking design experience.
• Knowledge of mobile attribution platforms (Adjust, AppsFlyer, or similar).
• Willingness to experiment with LLM for data automation.

Culture & Environment: Small teams with big ownership and minimal bureaucracy. Work with senior people focused on results over titles. Prefer clear thinking and quick decisions over endless meetings. Comfortable wearing multiple hats as needed.

Work Style: Analytics-driven decision making rather than chart production. Problem-solving orientation where numbers that don't make sense trigger investigation.