Product Data Engineer
T
TuoTempoHealthcare SaaS
Italy or SpainFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 2+ years of experience
- Required Skills
- PythonSQLApache AirflowGCPLooker
Requirements
- 2+ years of experience in Data Engineering or a similar role
- Hands-on experience designing, scheduling, and maintaining ETL pipelines using Apache Airflow
- Strong SQL skills
- Solid understanding of data warehousing concepts (preferably Google BigQuery)
- Proficiency in Python for ETL development and automation
- Experience working in AI product environments, supporting data needs for AI features such as experimentation, monitoring, and analytics
- Experience integrating data from multiple sources (APIs, databases, flat files, external platforms)
- Experience building dashboards or analytical views using BI tools (preferably Looker)
- Familiarity with Google Cloud Platform (GCP) services
- Strong analytical and problem-solving skills
- Comfortable working in a cross-functional, ambiguous environment
- Strong communication skills and ability to collaborate with both technical and non-technical stakeholders
- Strong interest in product data and how data drives product decisions
Responsibilities
- 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
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