обновлено 1 час назад
Analytics Engineer
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Analytics Engineer (SQL/ClickHouse/dbt): Building and maintaining analytical transformation layers, data marts, metric definitions, and semantic datasets for mobile game analytics with an accent on data quality, self-service analytics, and AI-driven tools. Focus on modeling UA, monetization, retention, and LTV data, reconciling metrics across sources, and designing reliable data access layers for AI agents.
Location: Remote work opportunities
Company
is a US mobile game publisher and developer creating global free-to-play mobile games, including Magic Jigsaw Puzzles, Puzzle Villa, Art of Puzzles, and Dominoes.
What you will do
- Design and maintain modular, incremental, tested, documented, and version-controlled analytical transformation models.
- Establish standards for analytics engineering, including transformation tooling, testing, code review, and CI.
- Define and reconcile company-wide metrics such as ROAS, cohort LTV, retention, ARPDAU, and spend across data sources.
- Build analytical datasets for user acquisition, monetization, creative performance, incrementality, dashboards, and reports.
- Model and document self-service datasets for product, user acquisition, and monetization teams.
- Build semantic descriptions, query interfaces, guardrails, and evaluation processes for AI-agent access to trusted data.
Requirements
- 3–5+ years of experience in analytics engineering, BI development, or data engineering with production ownership of a transformation layer.
- Strong SQL skills and experience with ClickHouse or willingness to develop deep ClickHouse expertise; experience with Postgres, BigQuery, or Snowflake is also relevant.
- Production experience with dbt, SQLMesh, Dataform, or an equivalent transformation framework, including modular models, testing, documentation, and CI.
- Strong analytical data modeling judgment and the ability to turn ambiguous business questions into data models through stakeholder collaboration.
- Experience with Git and code review, plus sufficient Python knowledge to automate work.
Nice to have
- Experience with mobile games or apps and metrics such as D7 ROAS, cohort LTV, ARPDAU, and retention curves.
- Practical experience with AI or LLM tools for data, including text-to-SQL, RAG over structured data, MCP, agent integrations, or model-output evaluation.
- Experience with Airflow, Dagster, Superset, or comparable orchestration and BI tools.
Culture & Benefits
- Remote work and a flexible schedule.
- Participation in the full product development cycle for global free-to-play projects.
- Career growth within an international company.
- Bonuses based on KPI achievement and project financial results.
- Paid conferences, training, language courses, and workshops.
- Access to psychologist sessions and charity projects.
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