A large insurance organisation is evolving its Azure data platform and strengthening the technical standards used by its Data Engineering teams. As Data Technical Lead, you will guide engineers working with Azure Synapse, Azure Data Factory, Mapping Data Flow, Databricks, PySpark, and SQL, while remaining hands-on with critical pipelines and new development.
The mission
Data Engineering teams build and operate pipelines across the ingestion, transformation, and consumption layers of the Azure ecosystem. The platform uses Azure Synapse, Azure Data Factory, Mapping Data Flow, Databricks, PySpark, and SQL to support structured data workloads and data warehouse operations. This work provides reliable, scalable data structures for reporting, analytics, and other business processes.
You will act as the senior technical reference for the Data Engineers and the main connection point with Data Platform Architects. Your scope combines technical decision-making, architectural alignment, implementation, peer review, and coaching across multiple teams. You will also design, develop, and optimise data pipelines, maintain existing components, and support the evolution of data engineering practices.
Your responsibilities
- Establish technical direction for Data Engineers and ensure implementation follows agreed architecture and engineering standards.
- Translate platform architecture guidelines into clear technical instructions for ingestion, transformation, and consumption pipelines.
- Design, develop, and optimise Azure data pipelines using Azure Data Factory, Mapping Data Flow, Azure Synapse, Databricks, PySpark, and SQL.
- Validate pull requests and peer reviews to improve code quality, maintainability, and compliance with data engineering standards.
- Strengthen performance, data quality, operational reliability, and the continuous improvement of the data platform.
- Coach junior engineers and provide structured feedback that supports consistent practices across teams.
Your profile
Essential skills
- Operates at senior level in data engineering, with the technical judgement to make and explain design decisions.
- Designs, develops, and optimises data pipelines within the Azure ecosystem.
- Demonstrates strong hands-on expertise with Azure Synapse, Azure Data Factory, Mapping Data Flow, Databricks, PySpark, and SQL.
- Applies dimensional modelling principles, including star schema design and data warehouse concepts, to build robust and scalable structures.
- Works effectively with data modelers and Data Platform Architects to align implementation with the target architecture.
- Communicates clearly with both technical and non-technical stakeholders, in writing and in discussion.
- Guides multiple teams through coaching, constructive feedback, and practical technical direction.
- Works autonomously with a structured, analytical approach and close attention to detail.
Preferred skills
- Uses Power BI to support reporting and analytics requirements.
- Understands semantic data modelling and its relationship to physical data structures.
Languages
- English: C1
- French: C1
- Dutch: B2