Full-Cycle Data Engineer

We're looking for a Full-Cycle Data Engineer to join our Data & AI team and own the flow from product data sources → modeling → dashboards → insights. You'll partner with product managers, engineers, and AI teams to turn raw product data into reliable analytics infrastructure that drives decisions across the company - from individual feature bets to CEO- and CFO-level questions.This is an end-to-end role: you'll take data products from ideation through engineering, analytics, and production deployment.ResponsibilitiesPipelines & infrastructure:Design, build, and deploy scalable data pipelines from product and system sources in production, using Python and orchestrators like Airflow.Work with distributed query engines such as BigQuery or Athena, with strong SQL throughout.Build and maintain semantic data models for large-scale operational systems and data lakes, manually or with tooling like dbt.Improve the end-to-end analytics stack, from ingestion to visualization, and collaborate with engineering on event tracking and instrumentation.Ensure data quality, consistency, and reliability across the stack.Analytics & reporting:Build and maintain dashboards and reporting layers in tools like Looker or Metabase, optimized for performance, usability, and clarityCreate self-serve analytics so product and business stakeholders can answer their own questionsSupport product experimentation: A/B testing, funnel analysis, feature adoptionPartnership & insight:Translate ambiguous questions from product leads, the CEO, the CFO, and others into clear metrics, KPIs, and analytical modelsSurface trends in usage and user behavior that influence the product roadmap and feature prioritizationProvide ad-hoc analysis and strategic reporting for leadership.Requirements: 5 years in data engineering, data analytics, or product analyticsStrong SQL and hands-on experience with large-scale datasets in cloud data warehouses (BigQuery or similar)Production Python experience for data pipelinesSolid grounding in product metrics, funnels, and user behavior analysisAbility to turn business questions into data models, metrics, and dashboardsStrong communication and cross-functional collaboration skillsNice to Have:Streaming or event-driven data systemsProduct instrumentation and tracking designAI/ML or LLM experienceHigh-scale SaaS or consumer product environments.This position is open to all candidates.