Software Engineer (Testing) - Private Markets

About Lantern

Lantern is a private markets data intelligence platform backed by the Aztec Group, Europe’s largest fund and corporate services provider.

We build data-driven products for private market GPs. As we scale, strong domain understanding is critical to ensuring financial data accuracy across our platform.

We are looking for someone with private equity or fund accounting experience who wants to transition into a technology role while leveraging deep domain expertise.

The Role

As a Software Engineer (Testing) – Private Markets, you will be embedded within cross-functional delivery teams and work closely with engineers, product managers, and other QA engineers.

Your primary impact will be strengthening data accuracy across the platform by translating private markets concepts into clear, testable logic. You will help define meaningful test cases, validate complex financial scenarios, and contribute to automated testing across the stack.

This role is ideal for someone with a strong background in private equity data who is curious, proactive, and motivated to build technical skills in automation, testing and software development.

You will initially work with support from experienced engineers and QA colleagues, with the expectation that you grow in independence over time.

Key Responsibilities

Translate Domain Knowledge into working, testable requirements and code

• Define robust test cases based on private equity and fund accounting concepts.
• Collaborate with software engineers to develop feature with high data quality.
• Validate financial data structures such as transactions, balances, reconciliations, and reporting outputs.
• Identify data accuracy gaps and clarify business rules with product and engineering teams.
• Ensure financial logic is correctly reflected in platform features.

Contribute to Automated Testing Across Layers

• Contribute to Playwright-based E2E tests for key user workflows.
• Support API-level and service-level testing of financial data flows.
• Help implement data validation checks to ensure integrity and consistency.
• Pair with developers to codify financial rules into automated tests.
• You are not expected to arrive as an expert developer, but you should be comfortable learning and contributing to code with guidance.

Strengthen Collaboration and Domain Depth

• Work closely with engineers and product managers on a daily basis to clarify financial concepts and edge cases.
• Support multiple squads where deeper private markets knowledge is required.
• Share domain understanding with other QA engineers and developers to raise overall financial literacy within the team.
• Proactively engage in discussions, ask questions, and challenge assumptions where financial accuracy is at risk.

Requirements

• Strong background in private equity, fund accounting, or private markets data.
• Solid understanding of financial data structures including transactions, balances, reconciliations, and reporting.
• Experience working with private equity data and/or fund accounting systems.
• Analytical mindset with strong attention to detail and data accuracy.
• Confidence working independently while remaining open to feedback and learning.
• Interest in building technical skills in automation, testing and software development.
• Some exposure to coding or scripting (any language) is desirable.
• Strong communication skills and a proactive attitude.

What Success Looks Like After 3–6 Months

• Financial logic is clearly defined and reflected in automated tests.
• Data accuracy gaps are reduced due to stronger domain-driven validation.
• You contribute confidently to automated tests across E2E, API, and data layers.
• Engineers and QA colleagues rely on you for private markets insight.
• You have meaningfully progressed in your technical capabilities.

Why This Role Is Different

This is not a traditional QA role and not a pure analyst position. It is a pathway into technology for someone with deep private markets expertise who wants to build engineering skills while making an immediate impact on data quality.