Data Architect

ABOUT US: As a world leading provider of integrated solutions for the alternative investment industry, Alter Domus (meaning “The Other House” in Latin) is proud to be home to 90% of the top 30 asset managers in the private markets, and more than 6,000 professionals across 24 jurisdictions. With a deep understanding of what it takes to succeed in alternatives, we believe in being different in what we do, how we work, and most importantly in how we enable and develop our people. Invest yourself in the alternative, and join an organization where you progress on merit, where you can speak openly with whoever you are speaking to, and where you will be supported along whichever path you choose to take.  Find out more about life at Alter Domus at careers.alterdomus.com   JOB DESCRIPTION: You will define the logical blueprint for a new commercial data platform — owning the data model, schema governance, taxonomy structures, lineage documentation, and master data strategy. You are the authority on  what the data means and how it relates — ensuring every entity, field, and relationship is defined with precision, governed through change control, and traceable from source to published output. You work closely with the Data Engineer (who builds the pipelines) and the Platform Engineer (who owns the physical infrastructure and delivery layer). Key Responsibilities: Data Lineage & Model Design:  Design the end-to-end logical data model — from raw source through transformation layers to client-facing outputs. Document full data lineage so every published metric can be traced back to source fields with a complete audit trail Schema & Taxonomy Governance:  Own the canonical schema for all data products. Manage version control, schema evolution (new fields, deprecations, breaking changes), and ensure consistency across multiple product lines Data Lineage & Traceability:  Implement metadata management and lineage tracking so that every benchmark, index value, and client report can be audited from published output back to source record Logical Integration Design:  Define how multiple data sources (primary administration data, regulatory filings, client-uploaded portfolios) integrate logically — entity matching rules, conflict resolution, and hierarchy management Governance Standards:  Establish naming conventions, documentation standards, data dictionaries, and classification rules. Own the technical governance framework that supports broader data governance and anonymisation committees Collaboration:  Partner with the Quantitative Director (who defines analytical requirements), the Data Engineer (who implements the physical pipelines), and the Platform Engineer (who provisions infrastructure and delivery mechanisms) Requirements: 8+ years in data architecture, data modelling, or master data management — ideally in financial services Deep expertise in logical and physical data modelling — dimensional modelling, Data…