The Opportunity
Design, build and operate enterprise-grade data infrastructure, reusable data pipelines and governed data assets that enable analytics, AI and business decision-making across the organization.
The role focuses on cloud-native data engineering using Google Cloud Platform, with strong emphasis on BigQuery, data quality, data governance, observability, performance and security by design.
As part of Technology Architecture, the Data Engineer contributes to shared data capabilities that support Data & AI Tech Factory delivery, business data domains, AI engineering and analytics teams across the enterprise.
What you'll get to do
Strategy & Roadmap
- Contribute to the evolution of the enterprise data platform and data engineering standards.
- Help define reusable patterns for ingestion, transformation, orchestration, monitoring and data productization.
- Support the modernization of analytics and AI data foundations on Google Cloud Platform.
- Promote cloud-first, governed and AI-ready approaches to enterprise data engineering.
- Identify opportunities to reduce duplication and increase reuse across data pipelines, datasets and platform components.
Delivery & Execution
- Design, build and maintain scalable data pipelines and data processing workflows using Google Cloud Platform services.
- Develop BigQuery data models, curated datasets and reusable data layers optimized for analytics and AI consumption.
- Create automated ETL/ELT processes to ingest, clean, enrich and transform data from multiple enterprise and third-party sources.
- Implement batch, near-real-time and event-driven data flows where appropriate, ensuring performance, reliability and operational resilience.
- Support integrations between cloud systems, on-premise systems and third-party applications where data movement or data availability is required.
- Build and optimize data workflows using services such as BigQuery, Cloud Storage, Pub/Sub, Cloud Functions, Cloud Run, Dataflow, Datap
📌 Data Engineer (España)
🏢 Puig
📍 España