Data Engineering Lead

Willis Re; Greater London; On-site; GBP 110,000 - 170,000; Full time

Job summary

Willis Re is building its data estate and seeking a Data Engineering Lead to architect and deliver a high-volume Snowflake platform in a fast-moving environment. You will mentor engineers, collaborate with architects and vendors, and shape data tagging, governance and quality across the business.

You will own end-to-end delivery from ingestion to curated data products, optimise cost and performance, and drive CI/CD, IaC and testing standards while aligning data strategy with risk and regulatory

Qualifications

• Proven track record leading delivery of a significant data platform end-to-end.
• Hands-on experience with Snowflake development and platform architecture.
• Experience directing partners and enforcing standards.
• Background in data tagging, cataloguing and governance.
• Strong data modelling, ETL/ELT skills and Azure-based tooling.

Responsibilities

• Snowflake Development: architect and build the platform, ingestion, transformation, data models and curated data products, with focus on performance and cost.
• Tagging & Cataloguing: establish and maintain tagging, classification and cataloguing for discoverability and labeling.
• Data Governance: own governance including ownership, lineage, access policies and cross-border residency.
• Data Quality: define data quality controls, automated testing, monitoring and reconciliation.
• Scale & Archival: design for high data volumes with partitioning, clustering, storage tiering and retention policies.
• Architecture Contribution: contribute to data architecture with architects to shape target-state designs.
• Vendor Leadership: direct and quality-assure work of strategic delivery partners and ensure standards.
• Engineering Standards: set CI/CD for data, automated testing, observability and IaC.
• Grow the Team: mentor engineers and help scale the data engineering function.

Skills

Leadership

Stakeholder communication

Data governance

Data modelling

Strategic thinking

Tools

Snowflake

Python

SQL

dbt

Terraform

Azure DevOps

Job description

Willis Re is building its global technology estate from the ground up, unencumbered by legacy and designed around data, analytics and modern cloud platforms. Our Snowflake data lake platform sits at the centre of that estate, and we are looking for a Data Engineering Lead to drive its implementation.

This is a deeply hands-on role. You will spend most of your time building on Snowflake and establishing how data is tagged, catalogued, governed and quality-assured across the business, working alongside our architects and directing strategic delivery partners who build with you.

Key Responsibilities

• Snowflake Development: Spend the majority of your time hands-on in Snowflake, architecting and building the platform and its surrounding ecosystem, including ingestion, transformation, data models, curated data products, and warehouse, performance and cost design for high-volume reinsurance placement, exposure, claims and market data.
• Tagging & Cataloguing: Establish and maintain data tagging, classification and cataloguing, so that data across the platform is discoverable, well described and correctly labelled for sensitivity and business meaning.
• Data Governance: Own governance for the platform, covering ownership and stewardship, lineage, access policies, retention obligations and cross-border data residency, working with security, risk and the business.
• Data Quality: Define and implement data quality controls, automated testing, monitoring and reconciliation, and make quality visible and measurable to data consumers.
• Scale & Archival: Design the platform to handle growing data volumes predictably, defining partitioning and clustering, storage tiering, retention and archival strategy, and keeping performance and cost under control as the estate grows.
• Architecture Contribution: Contribute to the data architecture, working with the Solution Architect and Head of Architecture & Engineering to shape target-state designs and feed real-world constraints back into them.
• Vendor Leadership: Direct and quality-assure the work of strategic delivery partners, reviewing their designs and code and holding them to the agreed standards.
• Engineering Standards: Set how the team builds, covering CI/CD for data, automated testing, observability and infrastructure-as-code.
• Grow the Team: Mentor engineers, raise the technical bar, and help shape how the data engineering function scales.

About You

You are a hands-on data engineering leader who is comfortable owning delivery in a fast-moving, greenfield environment with a lean core team and strategic delivery partners. Ideally you will bring:

• Experience: Proven track record in data engineering, including experience leading the delivery of a significant data platform end to end.
• Snowflake Depth: Deep, current, hands-on Snowflake expertise, having both built and architected across the platform and its surrounding ecosystem. This includes warehouse sizing, performance and cost optimisation, RBAC and access design, object tagging and masking policies, ingestion (Snowpipe, Streams and Tasks), sharing and marketplace, AI and ML capabilities such as Cortex, and transformation and orchestration tooling such as dbt.
• Governance & Cataloguing: A strong track record establishing data governance in practice, covering tagging and classification, data catalogues, lineage, stewardship and access policies.
• Data Quality: Practical experience implementing data quality frameworks, automated testing and monitoring, and driving measurable improvement.
• Data Modelling: Deep expertise in data modelling and warehouse design, with sound judgement on schema design, performance and cost at high volume.
• Scale & Archival: Proven experience running data platforms at high volume, including partitioning and clustering strategies, storage tiering, and defining retention and archival approaches that satisfy long-term regulatory obligations without runaway cost.
• Technical Stack: Strong SQL and Python, with practical experience of pipeline orchestration, ELT tooling, CI/CD (Azure DevOps or GitHub Actions) and infrastructure-as-code (Terraform/Bicep) on Azure.
• Architecture & Compliance: Enough architectural depth to shape platform design and challenge it constructively, and experience building to security and compliance requirements in regulated financial services.
• Vendor Delivery: Experience leading or quality-assuring work delivered by vendors and partners, including the ability to challenge designs constructively and enforce standards without direct authority.
• AI Foundations: Hands-on experience with Snowflake Cortex AI, or building AI and analytics use cases on data you have modelled yourself, is a significant advantage. Familiarity with AI-assisted engineering tools such as Claude Code or Claude Cowork is a plus.
• Leadership & Communication: Ability to lead engineers, influence stakeholders and explain technical trade-offs clearly to both technical and business audiences.

About Willis Re

We combine specialist broking with analytics, modeling and research to help insurers optimize risk transfer, strengthen balance sheets and achieve sustainable growth. Our approach is relationship-driven, transparent and outcome-focused.

At the heart of Willis Re is a focus on delivering the most cutting-edge analytical solutions to enable more informed, better decision-making for risk selection, portfolio optimization, and capital management.

The launch of Willis Re brings a strategic advantage of being unhindered by legacy, an ability to leverage data, statistical models and advanced technologies with the best knowledge and expertise to deliver more efficient and effective reinsurance outcomes. This places Willis Re in a unique position to build a truly analytically driven business, focused on creating solutions for the reinsurance industry that are future led and forward thinking.

Willis Re will also leverage recognized technical expertise from WTW’s Insurance Consulting & Technology business including their advanced modeling and analytical capabilities. Alongside this will be WTW’s Research Network, an award-winning business supporting and influencing science to improve the understanding and quantification of risk.

Willis Re is committed to embracing a diverse, inclusive, and flexible work environment. We provide equal opportunity to all qualified individuals regardless of race, colour, religion, age, gender, gender expression, national origin, veteran status, disability, orientation, or any other legally protected categories. If you have a need that requires accommodation, please email us at [e-mail]