Azure Data Engineer
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Summary
Hands-on Azure Data Engineer building and maintaining scalable, automated data pipelines end to end — ingestion, transformation, modelling, and delivery — on an Azure data platform using Data Factory, Databricks, Synapse, SQL, and Python/PySpark in an agile team.
Join a team building a modern Azure-based data platform. This hands-on engineering role involves designing and developing scalable, automated data pipelines using tools like Data Factory, Databricks, Synapse, and Logic Apps. You'll work across the full data lifecycle — from ingestion to transformation and delivery — enabling smarter, faster insights.
Key Responsibilities:
- Develop and maintain data pipelines using Azure services.
- Ingest, transform, and model data from diverse sources.
- Optimise data flows for performance and reliability.
- Support data quality and monitoring processes.
- Collaborate with cross-functional teams in an agile environment.
Collaboration With:
- Data Engineers, Architects, Product Owners, Test Analysts, and BI Teams.
Skills & Experience:
- Proficiency in Azure tools (Data Factory, Databricks, Synapse, etc.).
- Strong SQL and experience with data warehousing (Kimball methodology).
- Programming skills in Python, Scala, or PySpark.
- Familiarity with Power BI, SharePoint, and data integration technologies.
- Understanding of DevOps, CI/CD, and cloud concepts (IaaS, PaaS, SaaS).
- PowerShell scripting, containerisation, Semarchy MDM, NEC Housing, PL/SQL, and Total Mobile/Repairs solutions.