Data Engineer

About glas

GLAS is an international provider of institutional debt administration services, serving lenders, borrowers, issuers, and advisers offering a global platform across Loan Agency and related services, Capital Markets and Restructuring.

GLAS’ vision is to be recognised as the best-in-class independent, non-creditor, conflict-free provider of institutional debt administration services, enabling global clients and counterparties to achieve successful outcomes on their transactions.

The business currently comprises c.500 employees who deliver a solution-based, innovative service, ensuring GLAS is the preferred global partner of choice.

GLAS has a blue-chip customer base developed over many years; select clients include Apollo, Blackstone, CVC, Deutsche Bank and Goldman Sachs.

GLAS has been recognised as the premier independent provider of loan agency and bond trustee services with a portfolio of over $800 billion assets across its global platform.

The company is headquartered in London with offices in Paris, Frankfurt, Madrid, New York, New Jersey, Sydney, Melbourne, Brisbane, Singapore, Dubai, Hong Kong, Milan and Rome.

Our people are at the heart of GLAS's success.

We are committed to attracting, developing and retaining talented individuals in an environment built on inclusivity, diversity and opportunity.

We believe that diverse perspectives drive innovation, encourage meaningful discussion and help us deliver the best outcomes for our clients.

We are passionate about supporting our employees' career development and long-term success.

Our culture is underpinned by our core values of Excellence, Client Centricity, Collaboration and Innovation, which guide the way we work, support our clients and achieve results together.

At GLAS, we are committed to creating an environment where everyone has the opportunity to contribute, develop and thrive, regardless of background or experience.

We believe that fostering an inclusive workplace strengthens our business, our people and the service we provide to our clients

Responsibilities

• A key focus of the role is ensuring enterprise data is AI-ready, not only through strong data quality, governance, lineage and validation practices, but also by helping establish consistent business definitions, metadata, relationships and semantic structures that provide the contextual foundation required for AI, analytics and knowledge-driven solutions.
• You will contribute to the development of trusted data products and business ontologies that enable data to be discovered, understood and consumed consistently across Power BI, advanced analytics, Microsoft Copilot, AI agents and future AI-enabled solutions.
• Working closely with business stakeholders, system owners, BI developers and technology teams, you will contribute across the full delivery lifecycle, including solution design, development, testing, deployment, monitoring, documentation and production support, whilst adhering to GLAS security, governance and development standards.
• Support the migration and modernisation of data pipelines, storage and reporting workloads from Azure Synapse to Microsoft Fabric.
• Build and maintain Fabric Data Factory pipelines, Lakehouses, Warehouses, Notebooks, Dataflows and reusable data products.
• Implement scalable data architectures and engineering patterns, including Bronze, Silver and Gold data layers.
• Develop, optimise and troubleshoot SQL and T-SQL used within data pipelines, transformations, warehouses and reporting solutions.
• Design and maintain governed Semantic Models and curated datasets for Power BI and downstream consumers.
• Implement validation, reconciliation, monitoring and lineage processes to ensure data accuracy, consistency and trust.
• Support intelligent automation, AI-driven data quality controls and governed AI use cases using trusted enterprise data.
• Support workspace, capacity, deployment, gateway, monitoring and performance management activities.
• Implement and maintain role-based access controls, row-level security and appropriate data access controls.
• Contribute to source control, CI/CD pipelines, automated testing and controlled deployments using Azure DevOps.
• Monitor platform performance, investigate issues and maintain technical documentation.
• Translate business and reporting requirements into scalable and maintainable data solutions.

Requirements

• Hands-on experience with Fabric Data Factory, Lakehouse, Warehouse, OneLake, Notebooks, Dataflows and Semantic Models.
• Experience supporting or delivering migrations from Azure Synapse to Microsoft Fabric Advanced SQL: Strong SQL and T-SQL development, optimisation and troubleshooting skills.
• Experience building data processing and transformation solutions using Python and Spark.
• Strong understanding of ETL/ELT, data warehousing, dimensional modelling, orchestration and production support.
• Experience designing reusable semantic models, reporting datasets and data structures for analytics consumers.
• Experience implementing validation, monitoring, lineage, metadata and governed data access controls.
• Experience managing Fabric workspaces, capacities, security and performance optimisation.
• Experience with source control, CI/CD and automated deployment practices.
• Ability to engage effectively with both technical and non-technical stakeholders.

Preferred

• Experience working with regulated financial data, finance reporting, debt capital markets, loan administration or similar domains.
• Experience with Microsoft Copilot, Fabric data agents, Azure AI services, retrieval-augmented generation or related enterprise AI capabilities.
• Experience with Microsoft Purview, data cataloguing, master data management and enterprise data-quality frameworks.
• Experience applying analytical or AI techniques to data quality, anomaly detection or operational automation Cost Optimization: Understanding of Fabric capacity management and cost-efficient solution design .

Pay

Salary: Negotiable

Benefits

• Base salary + bonus Hybrid working 28 days annual leave + bank holidays Long service award Private Medical Insurance Private pension plan Life insurance plan Employee Assistance Program (EAP) Season ticket loan scheme Yearly eye examination Gym membership discount Career development and study support

Role location and working arrangements

• Data Engineer Location
• London
• Hybrid Working

What success looks like

• Synapse workloads are migrated to Microsoft Fabric through controlled, tested and supportable delivery.
• Fabric data products are secure, governed, reusable and performant.
• Data quality and validation controls identify issues earlier and reduce manual reconciliation.
• Semantic Models provide consistent business definitions across Power BI, AI and downstream consumers.
• AI-ready datasets are documented, traceable and suitable for responsible use by Copilot and agentic solutions.
• Agentic workflows and intelligent automation reduce manual effort without weakening governance or control.
• Platform monitoring, documentation and operational support improve reliability and resilience.