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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Architect - **Company:** Pharos Resource Partners - **Location:** UK - **Contract:** Permanent contract - **Skills:** BigQuery, Cloud Database, Data Architecture, Data Dictionary, Data Governance, Data Infrastructure, Data Warehousing, Database Queries, Dimensional Modeling, Entity Relationship Models, Metadata, Meta-Data Management, Reference Data, SQL Databases, Technical Data Management Systems, Snowflake, Data Lineage, Collibra, Performance Monitor, Data Management, Physical Data Models, FpML, Azure Synapse Analytics, Data Pipelines, Databricks - **Published:** August 26, 2026 - **Apply:** https://www.collegerecruiter.com/job/2815045166-data-architect ## About the Role * 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 ## Description 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 ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Making Data Warehouses fast. 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