<h3>Context</h3>
<p><strong>Elaia Partners</strong> is a European venture capital fund strengthening the first layer of its data infrastructure: a centralized, governed repository that consolidates portfolio and fund data from four primary sources across portfolio management, fund accounting, valuation, and banking/cash flow systems.<br>The goal is to create a single source of truth that can be queried by internal teams through Claude and other AI agents, while ensuring strict data access control at every level — including when queries come through automated agents.<br>This is Phase 1 of a broader data platform project. The focus is on connectivity, storage, data governance, custom financial calculations, and secure data exposition.</p>
<h3>Missions</h3>
<p>The engineer will be responsible for:</p>
<ul>
<li>Connecting four data sources into a single repository:  <ul>
<li>A portfolio CRM system  </li>
<li>A portfolio management system  </li>
<li>A banking / cash flow data source</li>
</ul>
</li>
<li>Defining update and storage rules:  <ul>
<li>Ingestion frequency: daily, quarterly, on-demand  </li>
<li>Versioning strategy and data retention policies  </li>
<li>Storage layer structure: raw / staging / certified marts</li>
</ul>
</li>
<li>Implementing Access Control Lists (ACLs) to ensure that every user — including when querying through Claude or other AI agents — can only access data they are authorized to see. ACL enforcement must apply at the data layer, not just at the application layer.  </li>
<li>Building financial calculations:  <ul>
<li>Fund-level: DPI (gross and net), TVPI (gross and net), IRR (gross and net), MOIC, J-curve  </li>
<li>NAV (per fund and per share class), A share values and carried interest mechanics  </li>
<li>Management fee calculations, capital calls and distributions tracking  </li>
<li>Portfolio company KPIs: revenue, EBITDA, EBITDA margin, growth rates, ownership %, current and projected valuations  </li>
<li>Time series on all key metrics at quarterly granularity</li>
</ul>
</li>
<li>Exposing the data by delivering a structured, documented, queryable data layer suitable for consumption by internal tools and AI agents.</li>
</ul>
<h3>Tools &amp; Environment</h3>
<ul>
<li>Cloud infrastructure  </li>
<li>SQL and Python  </li>
<li>Modern transformation layer (dbt or equivalent)  </li>
<li>RBAC / ACL systems at the database level  </li>
<li>REST APIs and file-based sources (CSV, XML, Excel)  </li>
<li>Financial data structures and fund mechanics (VC/PE context)  </li>
<li>Coding Agents principles, coding rules, CI/CD</li>
</ul>
<h3>Working Conditions</h3>
<ul>
<li>Format: Freelance / mission-based  </li>
<li>Duration: Phase 1 — to be discussed  </li>
<li>Availability: Near-term start preferred  </li>
<li>Location: Paris  </li>
<li>All data and infrastructure hosted in the European Union (GDPR compliance)  </li>
<li>Deliverables must be documented and maintainable  </li>
<li>Strict confidentiality applies to all data and project materials</li>
</ul>

Alexis Frentz

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Freelance Back-End Engineer - Data Infrastructure

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