Senior Analytics Engineer

Playbook is a leading creator platform for fitness, health, and wellness. Their mission is to help fitness creators build sustainable businesses while enabling hundreds of thousands of users to live healthier lives. They operate as a remote-first, product-driven team in the fitness tech space.

• 5+ years of experience in data engineering, analytics engineering, or a hybrid role with ownership of a data warehouse in production.
• Expert-level SQL and deep experience with BigQuery or comparable cloud warehouses (Snowflake, Redshift, Databricks).
• Hands-on experience with Dataform or dbt for building modular, tested, documented ELT pipelines and enforcing codebase conventions.
• Strong grasp of dimensional modeling including facts, dimensions, slowly changing dimensions, incremental models, and normalization decisions.
• Fluent with CI/CD for data including Git workflows, environment separation (dev/staging/prod), automated tests, and deployment pipelines.
• Experience with managed ingestion tools like Hevo or similar, with intuition for when to build custom solutions.
• Hands-on experience with Metabase and understanding of its impact on warehouse design; familiarity with other BI tools (Tableau, Power BI, AWS QuickSight) is a plus.
• Product-minded engineering approach considering performance, API shape, and data contracts for end-user consumption.
• Experience working with LLMs / AI in data workflows for modeling, documentation, SQL generation, or natural-language interfaces.
• Excellent communication skills in English to explain technical trade-offs to non-technical stakeholders and collaborate cross-functionally.
• Ownership mindset comfortable with decision-making under incomplete information and accountability for outcomes.

Nice to have:

• Prior experience in Data Engineering or BI Engineering roles.
• Strong understanding of SaaS and subscription business models including MRR, ARR, churn, deferred revenue, LTV, CAC, and edge cases.
• Experience in creator economy, marketplace, or subscription platforms.
• Experience building or integrating experimentation / A/B testing infrastructure.
• Experience with Python for ad-hoc data work, custom ingestion scripts, or orchestration.

• Design and build Playbook's data warehouse from the ground up in Dataform or dbt on BigQuery, defining raw/staging/intermediate/marts architecture, modeling conventions, naming, and testing standards.
• Own and manage the ingestion layer, extending Hevo setup across multiple data sources including Stripe, production Postgres (AWS), Mixpanel, GA4, HubSpot, Meta Ads, Google Ads, Ahrefs, PostHog, and new sources.
• Establish CI/CD, testing, and data quality practices for the warehouse including environments, automated tests, lineage, freshness checks, and alerting.
• Partner with the Growth team to translate their questions into production-grade data models, define and codify business metrics (MRR, churn, LTV, CAC, activation, retention, attribution), and enable self-serve analytics.
• Own, build, and evolve Playbook's creator-facing analytics product that powers metrics and insights for creators about their business performance.
• Support product and engineering teams on data-heavy features by partnering on data models, pipelines, and metric definitions.
• Triage, prioritize, and solve data requests across the company or invest in scalable models.
• Maintain and evolve the BI layer ensuring dashboards and reports are trustworthy, documented, and built on modeled data rather than raw tables.
• Set the direction for Playbook's data platform including build vs. buy decisions and stack evolution as the company grows.