About the role

Senior Data Engineer responsible for developing lakehouse architecture and robust data pipelines. Collaborating with teams to deliver business-ready data products on Microsoft Fabric.

Responsibilities

Design, build and own the Bronze → Silver → Gold lakehouse architecture in Microsoft Fabric, following medallion design principles for progressive refinement of data.
Develop robust, idempotent data pipelines with data quality checks and validation at each tier boundary.
Define and maintain data products, data models, ownership boundaries, SLAs and documentation for the Data Hub platform.
Work with architects and stakeholders to define and follow data architecture standards across the platform.
Ensure data accuracy, completeness and consistency across data sources, transformation layers and consumer interfaces.
Identify, troubleshoot and resolve data‑related issues in pipelines, schemas, transformations and downstream consumption.
Collaborate closely with Data Scientists, Data Analysts and business units to understand data requirements and deliver fit‑for‑purpose data products.
Provide technical guidance and support on data‑related topics across teams.
Document data flows, schemas, transformations, pipelines and operational processes to support maintainability and team scalability.

Senior‑level profile with proven hands‑on delivery experience in data engineering and technical ownership of production data platforms.
Able to work independently and take technical ownership.
Strong communication skills and experience working in cross‑functional teams.
Deep experience with PySpark, Spark SQL and Delta Lake, including partitioning strategy, MERGE patterns, and batch versus streaming trade‑offs.
Production experience with Microsoft Fabric or Azure Databricks.
Hands‑on experience with Azure data platforms, including Azure Synapse, Microsoft Fabric, and active development experience in Databricks for pipelines and optimization.
Strong understanding of event‑driven patterns for data ingestion; experience with Azure Event Hubs is a strong plus.
Solid understanding of data modelling and database design for analytics and business consumption.
Experience with version control and CI/CD practices using GitHub Actions, which is commonly used for Azure and Fabric‑related deployment workflows.
Good knowledge of Azure cloud services and data platform services.
Ability to think in terms of data products and domain ownership, and to define clear interfaces between platform teams and consuming teams.
Strong operational mindset for running and supporting pipelines in production.