Pharos Resource Partners
Data Architect
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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
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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
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