Senior Analytics Engineer

We're looking for a product-minded Analytics Engineer who treats data as a first-class product and thrives at the intersection of engineering, analytics, and game development. You are someone who can independently design, build, and evolve data products end-to-end, balancing technical excellence with real-world usability and business impact. What You'll Do Collaborate with engineers, product teams, and analysts to develop self-serve insight products that are responsive, precise, and scalable at petabyte levels Oversee the entire data product lifecycle, including designing new tracking plans, developing data models, ELT pipelines, and self-serve insight products like Looker explores and dashboards Build and maintain data products around technical KPIs that inform mobile game performance at scale—including crash rates, ANRs, latency, network errors, app size, and startup time—as well as internal engineering health metrics like build times, CI performance, and infrastructure costs Integrate, model, and maintain data from third-party tools such as Datadog, Bugsnag, crash reporting platforms, and other observability vendors, ensuring these external sources are reliable, well-documented, and seamlessly woven into the broader data ecosystem Act as a guardian of data quality, ensuring consistent metric reporting across a wide range of data products Establish and maintain robust data observability practices—including automated data validation, anomaly detection, SLAs, and alerting—to ensure trust and reliability across the pipeline Leverage AI and LLM-powered workflows across all stages of analytics engineering—from requirements gathering and SQL generation to data analysis, verification, and documentation—continuously improving team productivity and output quality Utilize cutting-edge technology stack including BigQuery, dbt, and Looker Provide technical leadership and empathize with game product teams and departments to enhance their daily operations and product success Bring expertise in a specific part of the data stack and lifecycle while contributing broadly across all aspects Mentor team members and drive the adoption of best practices within the team Design data products with the end user in mind, prioritizing usability, discoverability, and long-term adoption across product and business teams Proactively identify gaps, risks, and opportunities in existing data products and instrumentation, and drive improvements with a product-ownership mindset What We're Looking For A strong passion for solving complex analytical puzzles Proven ability to translate business needs into advanced analytics solutions Deep expertise with the modern data stack (BigQuery, Snowflake, dbt, Looker, Airflow, GitHub, command line-based workflows) Exceptional SQL skills coupled with at least 5 years of relevant experience in data analytics or engineering roles Solid understanding of data modeling principles (e.g., Kimball methodology, star schemas) Understanding of technical KPIs and performance metrics for mobile games at scale (e.g., crash-free rates, latency percentiles, app vitals), as well as familiarity with internal engineering metrics like build times, deployment frequency, and cost tracking Hands-on experience integrating and modeling data from third-party platforms (e.g., Datadog, Bugsnag, Firebase Crashlytics, or similar crash reporting and observability tools), including managing ingestion pipelines, schema evolution, and vendor-specific data quirks Hands-on experience with data observability frameworks and data validation methods (e.g., dbt tests, schema testing, anomaly detection, SLAs/SLIs, lineage tools) A strong product mindset, with experience designing data products as user-facing solutions rather than one-off analyses Demonstrated ability to work effectively with cross-functional stakeholders, balancing technical constraints, business needs, and delivery timelines A high level of ownership and autonomy, with c ... (truncated, view full listing at source)