Data Architect

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

• 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

#J-18808-Ljbffr…