- Design, build, and maintain reliable end-to-end ETL pipelines orchestrated with Apache Airflow
- Integrate data from multiple sources (internal operational databases, third-party APIs, SaaS tools) into the Google Cloud Data Warehouse (BigQuery)
- Design and evolve data models, warehouse schemas, and transformations to support scalable analytics and KPIs
- Ensure data quality, reliability, and observability through monitoring, validation, and alerting
- Own the product data structure, mapping product features and behaviors to analytics-ready data models
- Define and maintain meaningful KPIs in collaboration with Product and BI
- Enable analytics for AI-powered product features, ensuring visibility on usage, performance, quality, and business impact
- Partner with Product, BI, and other stakeholders to gather requirements and deliver dashboards and reports
- Maintain clear and up-to-date documentation for data models, pipelines, and metrics
- Act as the primary bridge between Backend Engineering and BI, owning the flow from data production to analytics consumption
- Triage, analyze, and address BI requests related to data availability, correctness, performance, and modeling
- Collaborate with Backend Engineers on data contracts, schema evolution, and performance optimization
- Proactively identify and resolve data-related issues impacting BI and Product teams
- Own first-level monitoring and support for data pipelines and Airflow DAGs, ensuring timely resolution of failures
- Collaborate with BI and Backend teams to troubleshoot and resolve complex issues
- Continuously improve the stability, performance, and maintainability of the data platform
PythonSQLApache Airflow+2 more