Data Engineer

GLAS; City Of London; Hybrid; GBP 70.000 - 110.000; Vollzeit

Benefits dieser Stelle

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

Zusammenfassung

GLAS is seeking a data engineer to lead the migration of enterprise data workloads from Azure Synapse to Microsoft Fabric. You will design and implement Fabric Data Factory pipelines, lakehouse and semantic models to power reporting, analytics and AI-enabled capabilities.

Working with stakeholders across finance and tech, you will ensure data quality, governance and scalable data architectures while following GLAS security standards.

Qualifikationen

• 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
• 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.

Aufgaben

• Fabric migration: Support the migration and modernisation of data pipelines, storage and reporting workloads from Azure Synapse to Microsoft Fabric.
• Data engineering: Build and maintain Fabric Data Factory pipelines, Lakehouses, Warehouses, Notebooks, Dataflows and reusable data products.
• Data architecture: Implement scalable data architectures and engineering patterns, including Bronze, Silver and Gold data layers.
• SQL development: Develop, optimise and troubleshoot SQL and T-SQL used within data pipelines, transformations, warehouses and reporting solutions.
• Semantic modelling: Design and maintain governed Semantic Models and curated datasets for Power BI and downstream consumers.
• Data quality and governance: Implement validation, reconciliation, monitoring and lineage processes to ensure data accuracy, consistency and trust.
• Automation and AI enablement: Support intelligent automation, AI-driven data quality controls and governed AI use cases using trusted enterprise data.
• Fabric administration: Support workspace, capacity, deployment, gateway, monitoring and performance management activities.
• Security: Implement and maintain role-based access controls, row-level security and appropriate data access controls.
• DevOps and release management: Contribute to source control, CI/CD pipelines, automated testing and controlled deployments using Azure DevOps.
• Operational support: Monitor platform performance, investigate issues and maintain technical documentation.
• Stakeholder engagement: Translate business and reporting requirements into scalable and maintainable data solutions.

Kenntnisse

Microsoft Fabric

Fabric migration

Advanced SQL

Python and Spark

Data engineering fundamentals

Power BI Semantic Models

Data quality governance

Fabric administration

DevOps

Communication

Tools

Azure Synapse

Microsoft Fabric

Jobbeschreibung

Location: London

Salary: Negotiable

Hybrid Working

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.

Reporting to the Lead Data Engineer, you will play a key role in GLAS's transition from Azure Synapse to Microsoft Fabric, supporting the development of a secure, scalable and governed enterprise data platform.

You will design, build and support Microsoft Fabric solutions, including Data Factory pipelines, Lakehouses, Warehouses, Notebooks, Dataflows and Semantic Models that enable reporting, analytics, automation and AI-driven capabilities. You will also leverage AI-assisted engineering techniques and automation to accelerate migration activities, improve productivity, enhance testing and validation processes, and support the efficient delivery of modern data solutions.

THE ROLE

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.

Key Responsibilities

• Fabric migration: Support the migration and modernisation of data pipelines, storage and reporting workloads from Azure Synapse to Microsoft Fabric.
• Data engineering: Build and maintain Fabric Data Factory pipelines, Lakehouses, Warehouses, Notebooks, Dataflows and reusable data products.
• Data architecture: Implement scalable data architectures and engineering patterns, including Bronze, Silver and Gold data layers.
• SQL development: Develop, optimise and troubleshoot SQL and T-SQL used within data pipelines, transformations, warehouses and reporting solutions.
• Semantic modelling: Design and maintain governed Semantic Models and curated datasets for Power BI and downstream consumers.
• Data quality and governance: Implement validation, reconciliation, monitoring and lineage processes to ensure data accuracy, consistency and trust.
• Automation and AI enablement: Support intelligent automation, AI-driven data quality controls and governed AI use cases using trusted enterprise data.
• Fabric administration: Support workspace, capacity, deployment, gateway, monitoring and performance management activities.
• Security: Implement and maintain role-based access controls, row-level security and appropriate data access controls.
• DevOps and release management: Contribute to source control, CI/CD pipelines, automated testing and controlled deployments using Azure DevOps.
• Operational support: Monitor platform performance, investigate issues and maintain technical documentation.
• Stakeholder engagement: Translate business and reporting requirements into scalable and maintainable data solutions.

Must-have Skills And Experience

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

Desirable Skills And Experience

• Financial services: Experience working with regulated financial data, finance reporting, debt capital markets, loan administration or similar domains.
• Microsoft AI ecosystem: Experience with Microsoft Copilot, Fabric data agents, Azure AI services, retrieval-augmented generation or related enterprise AI capabilities.
• Data governance: Experience with Microsoft Purview, data cataloguing, master data management and enterprise data-quality frameworks.
• Machine learning and advanced analytics: 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.

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.

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

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.