Graduate Data & Platform Engineer- PE Firm-CTO office

Our client is a PE firm with investment activities spanning private equity and other emerging-market strategies. Their current assets under management is US$1.6 billion. The business is transforming itself into a digital and AI-driven platform. You will be one of the first two technology hires supporting the CTO & Chief Digital Officer in building that platform from the ground up.

This role owns the data foundation of the transformation. Private capital markets run on scattered, unstructured information which are typically deal pipelines in spreadsheets and inboxes, portfolio company financials in PDFs, investor records across systems, fund data held by third-party administrators. Your job is to turn that into a clean, governed, queryable data estate that every AI and digital product we build sits on top of.

Job Responsibilities:

• Map the data estate. Inventory what data the business holds, where it lives (CRM, fund administrator, accounting systems, data rooms, email, spreadsheets), who owns it, and what state it's in.
• Build the data platform. Design and implement pipelines that ingest deal, portfolio, and investor data into a central warehouse; define schemas and data models for private markets entities (funds, deals, portfolio companies, investors, valuations).
• Integrate core systems. Build and maintain integrations with the CRM, fund administration, accounting, and document/data-room platforms via their APIs.
• Clean and govern. Establish data quality checks, deduplication, entity resolution (the same company spelled four ways), and access controls appropriate to sensitive LP and deal data.
• Serve the AI layer. Work with the Graduate AI & Product Engineer to expose clean, well-documented data to AI workflows to document extraction targets, retrieval indexes, reporting datasets.

Job Requirement:

• A degree (2:1 or above, or equivalent evidence of ability) in computer science, engineering, maths, physics, or a similarly quantitative field or a demonstrable self-taught equivalent.
• Solid programming ability in Python and SQL: you can show us code you've written (coursework, internships, personal projects).
• An instinct for structure: you enjoy turning messy information into clean, well-modelled data.
• Care and discretion: you'll handle commercially sensitive financial data and must take security and confidentiality seriously.
• Ability to work with ambiguity: this is a small team defining things as it goes, not a rotation programme with a syllabus.

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