Senior Data Engineer designing and improving software for business capabilities at Barclays. Collaborating with teams to build a data and intelligence platform for Equity Derivatives.
About the role
- Data Engineer at Destinus developing the data platform to support production and analytics needs. Involves migrating Excel sources to Lakehouse and integrating ERP systems in a hybrid role.
Responsibilities
- Own and maintain the Microsoft Fabric Lakehouse, ensuring data availability, integrity, and performance across all connected domains.
- Migrate existing Excel-based data sources into the Lakehouse through automated pipelines (Dataflow Gen 2), eliminating manual data handling.
- Integrate new data sources as reporting demand grows across the organisation—including Excel and SharePoint files today, and additional systems such as quality management tools as they are introduced.
- Ensure operational data integrates cleanly with ERP data (Microsoft Dynamics D365 F&O) already present in the Lakehouse, enabling unified reporting.
- Collaborate closely with the Operations Data Specialist and BI users to ensure the data layer meets downstream dashboard and analytics needs.
- Implement data quality checks, monitoring, and alerting to proactively catch pipeline failures or data drift.
- Document data models, pipeline logic, and transformation rules to ensure long-term maintainability.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
- 2–4 years of experience with data engineering, ETL/ELT pipeline development, or data platform management.
- Strong proficiency in SQL and experience working with relational and analytical data models.
- Experience with Microsoft Fabric, Azure Synapse, or comparable cloud data platforms.
- Familiarity with Power BI at the data model and semantic layer level (understanding how the BI layer consumes data, not necessarily building dashboards).
- Understanding of data governance, access control, and working in sensitive or classified data environments.
- Fluent in English, additional European languages are a plus.
- Experience in a start-up or scale-up environment is preferred.
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