Backend Software Intern (Data Architecture) — Remote

Company

Finprojections

finprojections.com

Designation

Backend Software Intern (Data Architecture) - Remote

Date Listed

08 Jul 2026

Job Type

Entry Level / Junior Executive

Intern/TS

Job Period

Immediate Start, For At Least 3 Months

Profession

IT / Information Technology

Industry

Finance

Location Name

Singapore

Work from Home

Allowance / Remuneration

$500 - 800 monthly

Company Profile

About Us

Finprojections works with founders and investors to build exceptionally rigorous financial models and powerful systems of financial control and reporting. For startups, we provide customized financial modeling and Virtual CFO services. For investors, we provide due diligence, fund concept development, and portfolio modeling and valuation.

We are now building the next generation of our proprietary financial software, and this internship sits at the foundation of that build.

Job Description

About the Role

You will build the data foundation and architecture for our proprietary financial software. At its core it is a data aggregator for founders: it brings together their historical financial and operating data, helps them forecast, and manages their cap table. It also connects to Claude through MCP, so founders can run a growing library of AI skills against their own data.

That means the data underneath has to be clean and well-structured enough for both the application and AI to work with reliably - across many interconnected entities and figures that flow across months and feed into each other. Designing that data layer, before the full production build begins, is what this role is about.

You won't need a finance background. The financial logic is already fully specified in working Excel models and the existing software, and the founder will guide you on domain questions. Your job is to translate that into a well-designed database.

What You Will Do

Design and build the database and its architecture: the schema, the entities and how they relate, and the structure that turns today's scattered data into one properly organised whole.

Build support for monthly time-series forecast data, scenario versioning, and multi-tenant workspaces with role-scoped access.

Produce a full data dictionary: every field, its type, unit, source, and how it connects to the rest.

Document the business logic and write test cases with known inputs and correct outputs, so the numbers can be verified after the production build.

Build one working proof of concept: model a single module (likely the cap table) in a real database, load real data, and reproduce the current software's numbers exactly.

Work directly with the founder and the team, raise questions early, and make sensible calls where requirements aren't fully defined.

Requirements

Currently a third-year student in Computer Science, Software Engineering, or a related field; ideally with a prior internship or solid project work to show.

A builder with a passion for data architecture for AI use cases.

Strong backend engineering: you've built real server-side systems and worked hands-on with databases.

Strong relational data modeling and schema design (Postgres, MySQL, or similar - the modeling skill matters more than the specific database).

Able to read plain JavaScript and work out the data model and rules from existing code.

Clear technical writing: data dictionaries, specs, and notes another engineer can work from.

Careful about accuracy - with financial data, the numbers have to tie out exactly.

Awareness of multi-tenant SaaS data design (tenant isolation, role-scoped access).

Nice to Have

Experience with MCP (Model Context Protocol) or building integrations for AI tools.

Comfort with numbers and finance, or exposure to fintech, financial models, or accounting.

Time-series data modeling; comfort with JSON/JSONB and git.

What You Will Learn

How to design a production database and data architecture from the ground up - and own it.

Data architecture for AI use cases: structuring data so AI agents can work with it reliably through MCP.

How startups actually run financial forecasting, cap tables, and fundraising, with direct mentorship from the founder.

A portfolio-ready body of work: a real database and schema you designed and built.

Application Instructions

Send your CV and a short note to . Include a backend or data project you've built, ideally where the database design was your own. We care about that more than a polished CV.