Azure Data Engineer – Distributed Cloud

About the role

Devoteam is looking for an experienced Azure Data Engineer to join its Distributed Cloud team in Lisbon. You will design, build and optimise end‑to‑end data pipelines and ETL/ELT solutions using Microsoft Azure services, ensuring high availability, scalability and data quality.

Key responsibilities

• Design, build and maintain scalable data pipelines using Azure Data Factory and Azure Databricks.
• Develop and optimise data infrastructure on Azure, leveraging Azure Data Lake Storage for ingestion and storage.
• Implement and manage data warehousing solutions with Azure Synapse Analytics (SQL or Spark pools).
• Set up data quality checks, monitoring and validation across all Azure systems.
• Collaborate with Data Scientists and Data Analysts to prepare data for analytics and machine‑learning projects.
• Automate deployment, monitoring and testing of data pipelines using IaC tools (Terraform or ARM Templates) and CI/CD practices.
• Provide technical guidance on data architecture and technology choices within the Azure ecosystem.

Required profile

• 3+ years of experience as a Data Engineer building production‑grade pipelines.
• Hands‑on expertise with Azure Data Factory, Azure Data Lake Storage (Gen2) and Azure Synapse Analytics.
• Strong SQL skills and solid understanding of data‑warehousing concepts and data modelling.
• Proficiency in a programming language such as Python or Scala.
• Experience with Infrastructure‑as‑Code tools (Terraform or ARM Templates) and CI/CD pipelines.
• Good analytical and problem‑solving abilities, with a passion for continuous learning and data governance.

Required skills

• Azure Data Factory
• Azure Databricks
• Azure Data Lake Storage (Gen2)
• Azure Synapse Analytics
• SQL
• Python or Scala
• Terraform or ARM Templates
• CI/CD practices
• Data modelling & warehousing
• ETL/ELT frameworks
• Distributed systems concepts
• Azure Event Hubs (preferred)
• Azure Stream Analytics (preferred)
• Docker (preferred)
• Kubernetes / AKS (preferred)