About the Role
We are looking for a Data Engineer to build, extend, and operate cloud-native data pipelines as part of a large-scale Azure data platform. This role covers end-to-end pipeline development - from source system ingestion through Bronze–Silver–Gold transformation layers — along with configuration-based framework extensions, evaluation engine integration, and data quality gate management across multiple data domains.
Key Responsibilities
Design and build end-to-end data ingestion pipelines for multiple enterprise source systems using Fabric Dataflow Gen2 and Event Hub connectors
Implement Bronze–Silver–Gold Delta Table data layering following established schema and field mapping conventions
Write and maintain SQL evaluation logic in Synapse Analytics for automated control assessment across multiple data domains
Perform data quality validation, schema reconciliation, and lineage verification across all pipeline stages
Support parallel-run validation activities ensuring data consistency between automated outputs and source reports
Required Skills & Experience
3+ years of experience in data engineering, ETL/ELT development, and cloud data pipeline delivery
Strong hands-on experience with Microsoft Fabric (Dataflow Gen2, Lakehouse, Delta Tables) and Azure Synapse Analytics
Proficiency in SQL for complex data transformation, evaluation logic, and cross-domain queries
Experience building event-driven pipelines using Azure Event Hub and Event Grid
Familiarity with config-driven or metadata-driven data pipeline frameworks
Experience with Microsoft Purview for data lineage registration and catalog management is advantageous
Ability to work in sprint-based delivery environments with multiple concurrent workstreams
Strong attention to detail and ability to validate complex data flows end-to-end across multiple systems
