Data Architect - Chaucer Group

Job Role Summary This is a hybrid role that sits at the intersection of data modelling, data engineering, and data governance. Reporting into the CTG Architecture function, with dotted line management into the Data function, the role requires both the strategic vision to design enterprise-scale data architectures and the technical know-how to design robust data pipelines and integrations. The role has clear accountability for ensuring all data designs derived from changes and products align to our enterprise data strategy, defined principles and adherence to data standards.

The role plays a central role in shaping how data is structured, governed, and moved across the business - from market-facing transactional systems through to analytical platforms - working closely with underwriting, claims, actuarial, finance, and data teams. The role acts as a key bridge between Architecture, Data, and data delivery teams, ensuring consistent application of data standards and principes, preventing the creation of future data silos and technical debt.

Key Responsibilities

Data Architecture & Modelling

1. Design and manage enterprise data architecture, standards and principles, covering both operational and analytical data domains across Chaucer’s value chain (submission, risk, premium, claims, bordereaux, regulatory reporting).
2. Ensure all new data products and changes align to the enterprise data strategy and standards, with ownership across the target architecture design and supporting the data product roadmaps to prevent fragmentation and future technical debt.
3. Partner with portfolio architects to understand and assess the impact from new business initiatives across the enterprise data landscape.
4. Define and govern data modelling standards, selecting appropriate paradigms - model-first for structured analytical workloads, or data-first (data lakes and lakehouses) for flexible, high-volume, or unstructured data scenarios.

Data Engineering & Platform

1. Support the Head of Data Platforms in architecting and overseeing the delivery of batch ETL and ELT pipelines, selecting the most appropriate integration pattern for each use case.
2. Ensure alignment with Technology, Data Strategy, and tooling decisions across all initiatives.
3. Provide quality assurance for data engineers’ work, ensuring alignment with architectural patterns, coding standards, and the overall design.
4. Support the cloud migration and modernisation initiatives, particularly the transition from on-premises SQL Server / SSIS estate to cloud-native equivalents on Azure and Snowflake.

Stakeholder Engagement & Governance

1. Act as the primary data architecture authority, engaging with business stakeholders, technology leads, and external partners (including Lloyd's, brokers, coverholders, and third-party data providers).
2. Act as the primary interface between Enterprise Architecture, Data, and delivery teams, ensuring clear data architecture input into all design and delivery decisions.
3. Support the Head of Data Governance in embedding data ownership, classification, quality controls, and consistent enterprise data definitions at the architectural level.
4. Provide architectural guidance on enterprise data capabilities, including Master Data Management (MDM) and data governance tooling (e.g. Purview), ensuring consistent adoption across delivery teams.
5. Provide expert data advice to various stakeholders, communicating complex risks and solutions to both technical and non-technical audiences
6. Chair the Data Design Authority (DDA) and ensure consistent application and tracking of data standards, governance, and architectural guardrails across all initiatives.
7. Provide data architecture assurance and approval for new systems, integrations, and data solutions.
8. Identify, manage, and support mitigation of data technical debt and architectural risk across the estate.
9. Produce clear architectural artefacts - including enterprise data flow diagrams, conceptual data models, and integration design documents – suitable for both technical and non-technical audiences.
10. Support AI-enabled initiatives by ensuring data architecture enables scalable, high-quality, and governed data for AI use cases, and provide data architecture input into AI design and governance forums where required.
11. Evaluate technology infrastructure for Data risks and weaknesses and develop strategies to mitigate them.
12. Monitor key performance indicators (KPIs) to track the success of Data architecture initiatives. Continuously seek opportunities to improve efficiency and effectiveness.

Skills & Experience

Essential

1. Experience working within an Azure-native data platform (ADLS Gen2, Azure Synapse, Purview, ADF).
2. Proven expertise in data modelling across model-first (3NF, Snowflake, Star, Medallion) and data-first (Data Lake, Lakehouse) design paradigms - with the judgement to know which to apply when.
3. Exposure to AI and ML initiatives from a data architecture perspective (e.g. data readiness, governance, and platform integration).
4. Hands-on experience designing and delivering batch ETL/ELT pipelines using a combination of Snowflake, SQL Server, Azure Data Factory, SSIS, and/or Python.
5. Strong understanding of enterprise data architecture principles, including data standardisation, governance, and management of data technical debt.
6. Experience producing and maintaining enterprise-level data architecture documentation and artefacts.

Desirable

1. Experience within the Lloyd's and/or London insurance markets (Managing agents, Brokers, Coverholders, or Central services).
2. Familiarity with ACORD standards including GRLC, CRP, A4A or AL3.
3. Knowledge of Delegated Authority data flows including bordereaux processing.
4. Understanding of Lloyd's regulatory reporting requirements (e.g. Solvency II, Lloyd's RDS, SBF) and their implications for data architecture.
5. Familiarity with data mesh or data product operating models.
6. Relevant professional certifications (e.g. Snowflake SnowPro, Microsoft Azure Data Engineer Associate, TOGAF, DAMA CDMP).

Personal Attributes