G MASS

Financial Services

DataArchitect-CanonicalDataModelling&EDM

£75–110k ~AI est. London, England, United Kingdom CONTRACT
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Data Architect - Canonical Data Modelling & EDM at G MASS. Skills: Canonical data modelling, Enterprise data foundations, Snowflake implementation, Data governance. Define canonical data models. Evolve canonical data models”

What You'll Achieve.

Enable enterprise data model; Power scalable growth; Implement and adopt models; Accelerate model development

Industry & Context.

Financial Services
Problems you'll solve

Root cause analysis; Troubleshooting; Data quality analysis

What They're Looking For.

Must Have

5+ years experience, Experience with Snowflake, Experience with buy-side data domains, Experience with investment lifecycle, Experience with data governance, Experience with modelling fundamentals, Experience implementing models, Experience bridging modelling and engineering, Experience with Python or SQL

Nice to Have

Experience with MS Access, Experience with Charles River, Familiarity with ESG data structures, Experience with custody data exchange, Experience with SWIFT messaging, Experience with ISO 20022, Data architecture experience, Solution architecture experience, Experience with AI/ML data requirements, Experience with LLM use cases, Experience with streaming ecosystems, Experience with Kafka, Experience with Azure Event Hubs

What You'll Do.

Define canonical data models

Evolve canonical data models

Govern canonical data models

Model investment lifecycle

Establish model semantics

Establish entity relationships

Establish model identifiers

Establish model lineage

Establish model versioning

Define golden-source ownership

Document data lineage

Apply industry standards

Map industry standards

Evaluate open standards

Ensure ESG data structures

Lead modelling for ingestion

Harmonise investment data

Harmonise client data

Harmonise market data

Harmonise reference data

Harmonise operational data

Define data models for custody

Partner with Snowflake teams

Ensure models are implemented

Work across business units

Ensure models support reporting

Partner with ESG team

Model RI-specific data

Translate logical models

Produce implementation artefacts

Provide architectural input

Establish model governance

Define data quality rules

Embed data quality rules

How You'll Work.

Team & Collaboration

Cross-functional teams; Investment Management; Portfolio Management; Investment Operations; Distribution; Finance; Compliance; ESG/Responsible Investment team; Snowflake engineering teams; Technology engineering teams

Full Job Description

ace has been engaged by a leading UK-headquartered wealth and asset management firm to support a multi-year technology transformation programme. The organisation manages assets across discretionary wealth, Responsible Investment (RI), charity, and institutional mandates, and is undergoing significant change: custody outsourcing to a global custodian, consolidation of its data platform on Snowflake, and a strategic initiative to build enterprise data foundations that will underpin AI, analytics, and regulatory capability for the next five years. We are seeking an experienced Data Architect to define, evolve, and govern the canonical data models that will underpin the firm's investment, client, and operational data domains. This is a high-impact role focused on models that get implemented and adopted, not documentation only. The successful candidate will bridge modelling and engineering: translating logical models into implementation-ready artefacts consumed by Snowflake, downstream analytics, and integration layers. This role is critical to enabling the organisation to move from fragmented, siloed data to a coherent, governed enterprise data model that powers scalable growth. This is a full-time position for an initial 3-month contract, for a Q3 start date. **Responsibilities:** Canonical Data Modelling * Define, evolve, and govern enterprise canonical data models across the firm's core buy-side data domains: positions, valuations, transactions, orders, client/AUM data, reference data, ESG/RI data, and benchmarks. * Model the investment lifecycle end-to-end: order generation, execution, allocation, settlement, corporate actions, performance attribution, and accounting impacts (IBOR/ABOR). * Establish clear semantics, entity relationships, identifiers, lineage, and versioning across all canonical models. * Define golden-source ownership for each data domain and document data lineage from source system to enterprise model to consumption layer. Standards & Industry Fram

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