Data Engineer / Azure

Location: Portugal (Remote) Engagement: Contract We are looking for an autonomous, experienced Data Engineer to deliver reliable, scalable, production-ready data solutions in a complex enterprise environment. The role focuses on data ingestion, transformation, modelling, orchestration, quality, and governance across the Microsoft Azure ecosystem. Key Responsibilities You will develop and maintain data pipelines using Azure Databricks, ADLS Gen2, Delta Lake, Spark, PySpark, and Medallion Architecture. You will build and maintain dbt models, tests, documentation, and incremental materialisations, as well as create and monitor Airflow/Astronomer DAGs. The role will involve ingesting data through APIs, SFTP/files, and JDBC, implementing data models including SCD Type 2, surrogate keys, schema evolution, and reconciliation, and establishing data quality, metadata, lineage, and auditable delivery practices. You will also troubleshoot production issues, perform root-cause analysis, and follow modern engineering practices using Git, Pull Requests, automated validation, and CI/CD through Azure DevOps. Requirements Candidates should have at least 3 years of relevant Data Engineering experience or equivalent production expertise, with advanced SQL and strong Python skills. Strong production experience with Azure, Databricks, ADLS Gen2, Delta Lake, Spark, and PySpark is required, along with significant hands-on experience with dbt, Apache Airflow, and Astronomer. Knowledge of Scala, Databricks Notebooks, Databricks Jobs, data modelling, and data quality is expected. Experience with Azure DevOps, Git, Pull Requests, and CI/CD is also required. Nice to Have Experience with Unity Catalog, Microsoft Purview, Azure Monitor, Log Analytics, Microsoft Fabric, Power BI Semantic Models, Microsoft Entra ID, Azure Key Vault, Impala, legacy data lakes and pipelines, Tableau, or Pentaho will be an advantage. Relevant Azure, Databricks, dbt, or Astronomer certifications are also valued.