Data Architect

Data Architect / Data Modelling Consultant — Asset Management About the Role We are seeking an experienced Data Architect / Data Modelling Consultant to design and shape the enterprise data architecture underpinning our investment platform. This is a high-impact role for someone who combines deep technical data architecture expertise with a strong understanding of the asset management data landscape (securities, positions, transactions, benchmarks, pricing, risk, and performance data) Key Responsibilities • Design and own the conceptual, logical, and physical data models underpinning core investment data domains (instruments, positions, transactions, holdings, pricing, benchmarks, risk, performance, client/account data) • Define and evolve the firm's data architecture strategy, including data warehouse/lake design, data mesh or domain-oriented approaches, and integration patterns • Establish data modelling standards, naming conventions, and governance practices across the organisation • Partner with portfolio management, risk, compliance, and operations teams to understand data requirements and translate them into scalable architecture • Work closely with engineering teams to implement data pipelines, master/reference data solutions, and data quality frameworks • Lead or support evaluation and selection of data platforms and tools (cloud data warehouses, data catalogues, MDM solutions) • Ensure data architecture supports regulatory, risk, and reporting requirements (e.g., performance reporting, look-through, regulatory reporting) • Produce clear architecture documentation, data dictionaries, and data lineage/mapping artefacts • Provide thought leadership and mentoring to data engineers and analysts on modelling best practice • Support data governance initiatives, including data quality, metadata management, and stewardship processes What We're Looking For Essential: • Proven experience as a Data Architect / Data Modeller within asset management, investment banking, or financial services • Strong understanding of investment data domains: instruments/securities, positions, transactions, corporate actions, pricing, benchmarks, risk, and performance data • Expertise in data modelling techniques (conceptual, logical, physical; dimensional modelling, normalisation, entity-relationship modelling) • Hands-on experience with modern data platforms (e.g., Snowflake, Databricks, BigQuery, Azure Synapse) and data warehouse/lakehouse architectures • Strong SQL skills and experience with data modelling tools (e.g., ERwin, ER/Studio, dbt, SQL DBM) • Familiarity with industry data standards and vendor data models (e.g., FIX, FpML, Bloomberg, SimCorp, GoldenSource, RIMES, FINBOURNE/LUSID) • Experience with data governance, MDM, and metadata/lineage tools (e.g., Collibra, Alation, Informatica) • Excellent stakeholder management skills, able to bridge business and technical teams • Strong documentation skills, including data dictionaries, ERDs, and architecture diagrams Please apply within for further details.