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    <title>Data Platform Architect, Wealth Management - ARC IT Recruitment RSS Feed</title>
    <link>https://jobs.co.uk/job/data-platform-architect-wealth-management-arc-it-recruitment--f2da3a39-cda5-4e00-8781-2ae0dd614e17</link>
    <description>RSS feed for Data Platform Architect, Wealth Management at ARC IT Recruitment.</description>
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    <lastBuildDate>Sat, 11 Jul 2026 17:43:44 GMT</lastBuildDate>
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      <title>Data Platform Architect, Wealth Management - ARC IT Recruitment</title>
      <link>https://jobs.co.uk/job/data-platform-architect-wealth-management-arc-it-recruitment--f2da3a39-cda5-4e00-8781-2ae0dd614e17</link>
      <guid>https://jobs.co.uk/job/data-platform-architect-wealth-management-arc-it-recruitment--f2da3a39-cda5-4e00-8781-2ae0dd614e17</guid>
      <pubDate>Sat, 11 Jul 2026 11:52:38 GMT</pubDate>
      <description>Location: London | Salary: 10000-500000 Daily | Type: Contract | Data Platform Architect, Wealth Management London | Contract, initial 3 months (potential to extend) | Competitive day rate Lead the hands-on design and evolution of a shared enterprise data model across wealth and asset management divisions. This is the first phase of a multi-division build, integrating data from UK, European and Swiss operations into a single, governed model. You will work directly with senior technical and business stakeholders to bring structure to a genuinely greenfield problem. Key Responsibilities:  Lead the initial build-out of a unified data model spanning wealth and asset management across multiple divisions. Liaise with data governance functions and divisional data teams to keep the model consistent as it develops. Apply strong development governance: define how new elements are added to the model without breaking what''s already built, while work continues incrementally alongside other live projects. Work with an established reference ontology to align data domains and objects to industry standards. Contribute hands-on to data engineering and pipeline work where needed. Operate independently with minimal ramp-up time, picking up context quickly in a fas...</description>
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