Experteer Overview Por favor, asegúrese de leer completamente el resumen y los requisitos de esta posibilidad de empleo que se detallan a continuación. As Lead Data Engineer, you design and maintain robust data pipelines across the procurement domain, aligning with DevOps practices in Azure DevOps and GitHub. You own end-to-end data products from ingestion to the Gold layer, champion data quality and governance, and mentor cross-functional teams to deliver scalable, production-grade solutions. You will work with dbt, Databricks, PySpark, and CI/CD automation to enable reliable, observable data platforms. This role offers impact at scale and opportunities to shape data engineering standards in a global, science-driven environment.Compensaciones / Beneficios• Design and implement end-to-end data pipelines across Bronze, Silver, and Gold layers• Develop data ingestion from source systems via ETL and API methods• Build modular transformation frameworks with dbt, PySpark, SQL; create staging models and load metadata aligning with Data Vault 2.0• Design and maintain CI/CD and DevOps processes using Azure DevOps and GitHub Actions• Implement IaC and deployment automation for data platform resources (dbt jobs, Databricks workflows, clusters)• Establish monitoring, observability,



and operational excellence with proactive maintenance and incident resolution• Drive data quality, governance, and FAIR data principles across all platform layers• Provide technical leadership, collaborate with data engineers, modelers, stewards, BI developers, data scientists and business SMEsResponsabilidades• 5+ years of production-grade data pipeline experience• Strong dbt, SQL, Python, Spark (PySpark), Databricks, Git, Azure DevOps, and GitHub experience• Deep CI/CD and automation experience with Azure DevOps Pipelines and GitHub Actions• IaC knowledge (Terraform, Bicep) considered a strong advantage• Cloud data engineering expertise (Azure) with Databricks jobs, clusters, xqbhyrx and workflows in production• Extensive knowledge of Data Vault 2.0 architecture (Raw Vault, Business Vault, Gold)• Ingestion and integration patterns (ETL, incremental processing, CDC, API-based ingestion)• Data governance/quality experience with FAIR principles and data discoverability• Leadership and cross-functional collaboration skillsRequisitos principales• Unique career paths across health, nutrition, and beauty• Impact millions of consumers daily• Growth and leadership development• Collaborative culture• Voice matters and inclusion• Learning and mobility across businesses

📌 Lead Data Engineer (Cross Domain) (Barcelona)
🏢 Dsm
📍 Barcelona