Senior Data Engineer
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Role details
Tech stack
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Job description
The Senior Data Engineer designs, builds, tests, and supports the data pipelines and data products behind our analytics, reporting, and machine learning work on Azure and Microsoft Fabric. The role focuses on data engineering: ingesting, transforming, and modeling structured and unstructured data from sources such as Azure Synapse, Azure SQL, SQL Server, and ADLS Gen2. That data lands in Fabric Lakehouse and Warehouse on OneLake through Azure Data Factory, Fabric Data Factory pipelines, Dataflow Gen2, and PySpark notebooks. The engineer will also design and run machine learning (ML) pipelines with the Data Science team, automate builds and releases through Azure DevOps pipelines, and set up supporting Azure resources with Bicep templates. They will apply secure data practices (Managed Identity, Microsoft Entra ID, Key Vault, OneLake security, and Microsoft Purview) and build data quality, lineage, and governance into every pipeline. This role works closely with Data Scientists, Solution Architects, Software Engineers, DevOps Engineers, QA Engineers, Project Managers, Information Security Engineers, and Delivery Managers.
Requirements
- Microsoft Fabric (Lakehouse, Warehouse, Data Factory, Notebooks, OneLake)
- Azure Data Factory and ETL/ELT design
- SQL/T-SQL, Python, PySpark
- ML pipeline concepts (feature engineering, training, batch scoring, MLflow)
- Azure DevOps CI/CD pipelines
- Bicep / Infrastructure as Code
- Data Lake / Lakehouse and medallion architectur
Nice to have skills
- Azure Synapse Analytics and Azure Databricks
- Microsoft Purview
- Power BI semantic models and Direct Lake
- Fabric Real-Time Intelligence (Eventstream, KQL)
- GitHub Enterprise and fabric-cicd
- Experience migrating SAS workloads
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