MDW is a leading consulting company specialized in Data, AI and BizApps, with offices in Geneva and Madrid. Recognized as Microsoft Partner of the Year with multiple awards, we help major organizations transform their business with Azure, Microsoft Fabric, Databricks and AI technologies.

Las cualificaciones, habilidades y toda la experiencia relevante necesaria para este puesto se pueden encontrar en la descripción completa a continuación.
Your roleWe are looking for a Senior Data Engineer to join our team and work on cutting-edge Data projects.
What you will do
- Build and evolve Data Solutions on Azure & Microsoft Fabric
- Deliver real consulting projects across industries
- Provide personalized support to clients, working closely with them on-site in a hybrid model, ensuring effective collaboration and solutions that align with their business objectives
- Attend client and project-related meetings at Microsoft's offices in Madrid. As a Microsoft Partner of the Year, we work side by side with Microsoft teams, and you will be asked to join these sessions on-site on a regular basis




- Collaborate with an international team of experts in MDW to grow together

What we value
- Experience with Azure Data Platform (Data Factory, Synapse, Data Lake gen2, Azure Functions, Logic Apps, etc.)
- Knowledge of Databricks and Fabric platforms
- Strong skills in Python/PySpark and SQL
- Experience with CI/CD with Azure DevOps
- Knowledge of IaC with Terraform, Bicep, ARM or Pulumi
- Experience with batch data workflow design, such as Medallion Architecture
- Experience with data modelling: star schemas, snowflake
- Experience with Databricks asset bundles
- Strong client communication skills, ensuring effective management and a positive experience throughout the project
- Databricks certifications
- Experience working in an Agile environment
- Nice to have: real-time workflow design such as Kafka
- Nice to have: knowledge of structured streaming, Delta Live Tables, Fabric Eventhou

📌 Senior Data Engineer (Madrid)
🏢 MDW
📍 Madrid