Azure Data Engineer

Role & responsibilities

• Assess current Synapse Analytics workspace including pipelines, notebooks, datasets, and SQL scripts.
• Rebuild or refactor Synapse pipelines, notebooks, and data models using Fabric-native services.
• Collaborate with data engineers, architects, and business stakeholders to ensure functional parity post-migration.
• Validate data integrity and performance in the new environment.
• Document the migration process, architectural decisions, and any required support materials.
• Provide knowledge transfer and guidance to internal teams on Microsoft Fabric capabilities.

Preferred candidate profile

• Proven experience with Azure Synapse Analytics (workspaces, pipelines, dedicated/SQL serverless pools, Spark notebooks).
• 5 years of synapse azure cloud experience. 
• Probably only see 1 to 2 years experience in Fabric. 
• Hands-on experience with Microsoft Fabric (Data Factory, OneLake, Power BI integration).
• Strong proficiency in SQL, Python, and Spark.
• Solid understanding of data modeling, ETL/ELT pipelines, and data integration patterns.
• Familiarity with Azure Data Lake, Azure Data Factory, and Power BI.
• Experience with Lakehouse architecture and Delta Lake in Microsoft Fabric.
• Experience with CI/CD practices for data pipelines.
• Excellent communication skills and ability to work cross-functionally.

Nice-to-Have Skills:

• Familiarity with DataOps or DevOps practices in Azure environments.
• Prior involvement in medium to large-scale cloud platform migrations.
• Knowledge of security and governance features in Microsoft Fabric.
• Knowledge of Dynamics Dataverse link to Fabric.