We are looking for a Product Data Engineer to own and evolve our data platform at the intersection of Backend, BI, and Product.
This role is not purely analyst nor purely backend: it is a cross-functional ownership role responsible for ensuring that product data is reliable, well-modeled, and effectively consumed by BI and Product teams.
You will design and maintain ETL pipelines, collaborate closely with Backend and BI teams, and act as a bridge between data producers and data consumers, enabling high-quality analytics and product decision-making.
Key Responsibilities
Data Platform & Pipelines
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Design, build, and maintain reliable end-to-end ETL pipelines orchestrated with Apache Airflow.
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Integrate data from multiple sources (internal operational databases, third-party APIs, SaaS tools) into the Google Cloud Data Warehouse (BigQuery).
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Design and evolve data models, warehouse schemas, and transformations to support scalable analytics and KPIs.
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Ensure data quality, reliability, and observability through monitoring, validation, and alerting.
Product & Analytics Enablement
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Own the product data structure, mapping product features and behaviors to analytics-ready data models.
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Define and maintain meaningful KPIs in collaboration with Product and BI.
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Enable analytics for AI-powered product features, ensuring visibility on usage, performance, quality, and business impact.
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Partner with Product, BI, and other stakeholders to gather requirements and deliver dashboards and reports .
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Maintain clear and up-to-date documentation for data models, pipelines, and metrics.
Backend ↔ BI Bridge & Ownership
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Act as the primary bridge between Backend Engineering and BI, owning the flow from data production to analytics consumption.
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Triage, analyze, and address BI requests related to data availability, correctness, performance, and modeling.
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Collaborate with Backend Engineers on data contracts, schema evolution, and performance optimization, without owning core backend services.
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Proactively identify and resolve data-related issues impacting BI and Product teams.
Platform Health & Support
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Own first-level monitoring and support for data pipelines and Airflow DAGs, ensuring timely resolution of failures.
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Collaborate with BI and Backend teams to troubleshoot and resolve complex issues.
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Continuously improve the stability, performance, and maintainability of the data platform.