Senior Data Engineer

Help shape WTW's global data engineering capability and build trusted data platforms that power better business decisions.

Everything we do within WTW Global Technology has a global focus at its heart. We aim to provide colleagues with consistent technology, experiences and operations wherever possible.

As a Senior Data Engineer, you will play a key role in the design, development and support of WTW's central data engineering capability. Working closely with Architecture, Information Security, business teams and technology stakeholders, you will help define engineering standards, create reusable frameworks and enable teams across WTW to develop secure, scalable and trusted data solutions. You'll combine strong hands-on engineering expertise with a passion for building shared capabilities that accelerate analytics, AI and data-driven decision making across the enterprise. This role offers the opportunity to work with modern data platforms including Microsoft Fabric, Databricks and Azure technologies while helping shape the future of WTW's data landscape.

Work Style: Enjoy a flexible hybrid working model, with occasional travel to our London office for collaboration, team meetings, and key business activities.

The Role

• Design, build and support reusable data engineering frameworks, shared services and reference implementations used across WTW.
• Develop and maintain production-grade data pipelines, data models and datasets using Microsoft Fabric, Databricks and Azure technologies.
• Create reusable ingestion, transformation and data quality patterns that enable consistent data delivery at scale.
• Partner with Architecture and Information Security teams to ensure data solutions are secure, governed and compliant by design.
• Support data governance initiatives including data cataloguing, lineage, classification and stewardship.
• Design and operate batch and streaming data integration solutions across enterprise data sources.
• Enable analytics, reporting and AI use cases by delivering trusted, high-quality data products.
• Implement DataOps best practices including testing, monitoring, version control and observability.
• Troubleshoot and resolve production data platform issues, performing root cause analysis and remediation.
• Create and maintain technical documentation, standards and engineering guidance.
• Mentor and support other engineers through design reviews, knowledge sharing and technical leadership.
• Evaluate emerging technologies and contribute recommendations to improve WTW's data engineering capabilities.