Source description
About the role
5+ years experience in data engineering or a similar role in a commercial environment
Hands-on experience with Microsoft Fabric (Lakehouses, Notebooks, Data Pipelines, OneLake, SQL Analytics Endpoints) or equivalent depth in Azure Synapse Analytics
Advanced SQL for data transformation, performance tuning, and Delta Lake table management
Proficient in Python/PySpark for data processing, API integration, and pipeline automation
Proven experience building custom API connectors (REST, SOAP/XML) with OAuth 2.0, pagination, rate limiting, and incremental sync patterns
Strong understanding of Medallion Architecture, data lakehouse concepts, and Delta Lake (merge, upsert, soft-delete handling, time travel)
Experience with dimensional modelling (star/snowflake schemas) and Power BI semantic model development
Working knowledge of Azure services: Key Vault, Azure Monitor, Log Analytics, Azure AD/Entra ID
Experience translating business requirements into dimensional models iteratively (not just building pre-designed schemas)
Comfort operating autonomously with minimal supervision in a client-embedded model
Experience implementing row-level security in Power BI (DAX-based RLS, dynamic security models)
Familiarity with CI/CD in a Fabric context: Deployment Pipelines, Git integration, environment promotion workflows
Experience with semi-structured data formats (JSON, XML) and handling schema evolution across pipeline layers
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