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 SMEs

Responsabilidades

- 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, xugodme 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 skills

Requisitos 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