Data Architect

Pharos Resource Partners
UK
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

BigQuery Cloud Database Data Architecture Data Dictionary Data Governance Data Infrastructure Data Warehousing Database Queries Dimensional Modeling Entity Relationship Models Metadata Meta-Data Management
+13 more
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

Job 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

Requirements

  • 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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