Staff Product Data Analyst

ABOUT THE ROLE Hi, I'm Aurobind, Head of IT, Systems and Data at Jane. We're rebuilding how we manage data and analytics at Jane. Our goal is to establish a trusted data foundation that powers self-service analytics, AI, and consistent business metrics across the company. This role is focused on Product Analytics—but not in the traditional sense of generating insights or building dashboards. Instead, you'll focus on building the technical foundation that enables Product teams to answer their own questions with confidence. You'll partner closely with Engineering, Product, and Growth to improve product instrumentation, build scalable dbt models, standardize business logic, and create governed datasets that power reporting, experimentation, and AI. You'll also help establish the standards for how product data is modeled, tested, documented, and maintained as our analytics platform continues to evolve. If you enjoy solving complex technical problems, building scalable data foundations, and enabling others through trusted data, this role is a great fit. WHAT IMPACT WE’RE LOOKING FOR YOU TO MAKE - Build and maintain the product analytics data foundation that powers reporting, self-service, experimentation, and AI. - Partner with Engineering to define, implement, and validate product instrumentation before new features are released. - Design and maintain scalable dbt models that transform raw product events into trusted analytical datasets. - Build semantic models, standardized business logic, and governed metric definitions that ensure consistent product metrics across dashboards, self-service, and AI. - Develop certified datasets that power modern analytics and visualization platforms such as Looker, Omni, Hex, and similar technologies. - Partner with Product Managers to translate business requirements into scalable, trusted, and reusable analytical data models. - Monitor product data pipelines, identify instrumentation gaps and data quality issues, and implement scalable, long-term improvements. - Continuously improve how product data is modeled, governed, documented, and consumed across the analytics platform. - Leverage AI to accelerate analytics engineering workflows, including data modeling, testing, documentation, and code development. WHAT EXPERIENCE WE NEED - 6+ years of experience in Product Data Analyst, Analytics Engineering, or a similarly technical data role within a SaaS or high-growth technology company. - Expert-level SQL skills and deep experience designing scalable analytical data models, with a strong understanding of data architecture and query performance optimization. - 6+ years of experience building, deploying, and maintaining dbt projects in production environments. - Experience modeling behavioral product data and building event-driven analytical datasets. - Experience partnering with Engineering teams to define product instrumentation requirements and improve the quality and reliability of product event data. - Experience working with Customer Data Platforms (CDPs) such as Segment or RudderStack. - Experience designing semantic models, reusable business logic, governed datasets, and trusted metric definitions that enable consistent analytics across multiple consumption layers. - Experience implementing data quality testing, documentation, observability, and governance best practices. - Experience building or supporting modern analytics and visualization platforms such as Looker, Omni, Hex, Sigma, or similar technologies. - Strong understanding of how semantic models and governed metrics are consumed across dashboards, self-service analytics, and AI experiences. - Experience working with modern cloud data platforms such as Snowflake, BigQuery, or Redshift. - Experience using AI tools such as Cursor, Claude Code, or similar technologies to improve analytics engineering workflows. - Strong communication skills and the ability to partner effectively with Engineering, Product, Analytics, and business stakehol…