Role Overview

Own and maintain the physical data architecture across the core data estate, including schemas, tables, views, and modelling standards
Design and evolve conceptual, logical, and physical data models across core business and investment domains
Define and maintain canonical data models and shared entity definitions to support consistent cross domain reporting and analytics
Work closely with Data Stewards to define and maintain business vocabularies, canonical definitions, and domain concepts
Collaborate with Data Owners and Data Consumers to ensure data models accurately reflect agreed business meaning and usage
Translate business concepts into logical and physical data structures that can be reliably implemented by engineering teams
Act as a translator between business stakeholders and engineers, reducing ambiguity and rework caused by inconsistent interpretation of data
Define and maintain data architecture standards, modelling conventions, and reference patterns
Provide clear architectural guardrails that enable teams to deliver quickly while maintaining consistency and quality
Partner with engineering teams to ensure solutions align with agreed data architecture principles
Collaborate with governance and risk functions to ensure data designs are auditable, well documented, and compliant with organisational standards

Requirements

Demonstrable understanding of core asset‑management concepts and how they are represented as data, including financial instruments, transactions, positions and holdings, portfolios, benchmarks, pricing, reference data, and legal entities. Able to apply this understanding when designing data models, integration patterns, and data domains to ensure consistency, scalability, auditability, and regulatory alignment
Strong experience in conceptual, logical, and physical data modelling, with the ability to select appropriate modelling approaches based on use case and context
Proven ability to design and maintain enterprise and canonical data models spanning multiple business domains
Practical experience with dimensional and consumption‑oriented models for analytics and reporting
Ability to apply Data‑as‑a‑Product principles when defining data assets, including clear purpose, ownership, consumers, and quality expectations
Experience defining data architecture standards, patterns, and guardrails, and guiding teams through their adoption
Solid understanding of data governance, metadata, lineage, and regulatory expectations in a regulated environment
Experience working with modern data platforms, including cloud data warehouses and lakehouse architectures, from a data‑architecture and modelling perspective
Strong SQL and relational modelling foundations
Familiarity with data integration patterns, analytical data use cases, and layered data architectures (e.g. raw, curated, consumption)
Clear understanding of how modelling and architectural decisions impact cost, performance, scalability, and operability, and able to articulate and document associated trade‑offs
Able to work confidently with engineers, architects, data stewards, data owners, and non‑technical stakeholders, acting as a bridge between business meaning and technical implementation
Strong communication skills, with the ability to explain data structures, semantics, and architectural trade‑offs clearly
Consultative and influential, able to guide without direct authority
Pragmatic and outcome‑focused, comfortable balancing strategic intent, delivery realities, and cost considerations

Tech Stack

Cloud
SQL

Insight Investment

Open Positions (1)

Engineering

Data Architect