Senior Data Engineer (AI & Products)

Your mission We're looking for a Senior Data Engineer to build the data foundation that powers the next generation of AI-enabled business software. You will design, evolve, and expose product data so it can be reliably consumed by software products, AI services, and enterprise platforms, transforming existing product data models into scalable, well-governed Data Products while promoting engineering best practices, data quality, and reusable integration patterns.

This is a software engineering role focused on product data, distributed systems, and modern data platforms — not a Business Intelligence, Reporting, or Data Science position. Your work will directly enable AI capabilities (AI agents, RAG) and have a direct impact on the reliability and scalability of the data that powers products used by thousands of users in Spain.

Technologies & environments

• Cloud & data platform: Azure; Databricks, Delta Lake, Unity Catalog, Apache Spark
• Data products & modelling: Data Products, Data Mesh, domain-driven data modelling, Schema Registry
• Integration: event-driven architectures and enterprise messaging (Hermes)
• IaC, orchestration & governance: Terraform, Dagster, Liquibase; Witboost, Profisee
• Languages: Python, SQL (over transactional enterprise applications)
• Software engineering: REST APIs, Docker, Kubernetes, Git, CI/CD

What will you do?

• Analyze existing product data models and identify opportunities for improvement.
• Design and evolve domain-oriented data models aligned with product architecture, and define and publish reusable Data Products for multiple business domains.
• Define data contracts, ownership, and schemas together with Product Engineering teams.
• Design and implement data pipelines for operational and AI workloads, publishing and consuming data through the corporate Data Platform.
• Design event-driven integrations using enterprise messaging patterns.
• Work with AI Engineers to provide reliable data for AI features, AI agents, and Retrieval-Augmented Generation (RAG) solutions.
• Improve data quality, governance, and observability, and contribute to architectural decisions and reusable patterns across product teams.

Technical requirements

• 5+ years of experience in Data Engineering, with strong SQL and relational data modelling.
• Experience analyzing and evolving existing application data models in transactional enterprise software.
• Experience designing Data Products or modern enterprise data platforms, defining APIs, schemas, and data contracts.
• Hands-on experience building data pipelines in Python, with Databricks or Apache Spark.
• Experience with Azure cloud services and event-driven architectures.
• Understanding of Domain-Driven Design principles.
• Professional level of English, spoken and written