About Us
Lantern is a private markets data intelligence platform backed by the Aztec Group, Europe’s largest fund and corporate services provider.
We’re moving quickly to market with an innovative solution for private market GPs. As we scale, we’re strengthening our quality practices and looking for a Senior QA Engineer who can raise the bar across engineering and product.
If you care about modern testing, Continuous Delivery, and catching issues early, this role could be a strong fit.
The Role
You will join a cross-functional team building data-driven products within a microservice architecture of independently deployable services.
Reporting to the Lead QA Engineer, you will contribute to and evolve testing strategy within your services—strengthening E2E coverage, improving data validation, and helping teams detect issues as soon as they are introduced.
You will work closely with Engineering, Product, Design, Client Success, and subject matter experts to embed quality from discovery through release.
This is a highly collaborative role. You will proactively pair with developers, engage other QA engineers across services, and help create shared ownership of quality—bringing testing closer to development rather than operating as a downstream function.
Key Responsibilities
Embed Quality from Discovery to Release
- Participate in discovery and story kickoffs to clarify requirements and risks.
- Shape clear, testable acceptance criteria grounded in real usage.
- Define and align on required test cases for release within your service.
- Validate stories collaboratively with engineers and product, reducing handoffs and late surprises.
Strengthen Automated and E2E Testing
We are improving our E2E testing approach, where coverage and confidence are uneven.
- Contribute to a pragmatic E2E strategy focused on meaningful user workflows.
- Design and maintain Playwright-based E2E tests aligned with business-critical flows.
- Drive effective testing across layers (unit, integration, API, acceptance), ensuring the right coverage at the right level.
- Improve CI/CD signal quality so the pipeline remains the source of release confidence.
Improve Data Validation and Early Defect Detection
We operate in a data-intensive domain where accuracy is critical and some issues surface too late.
- Develop a strong understanding of how Lantern ingests, transforms, and serves data.
- Contribute to validating data accuracy, integrity, and consistency across services and applications.
- Work with engineers, product, client success, and SMEs to define explicit, testable data criteria.
- Introduce automated checks to detect anomalies early and participate in root cause investigations.
- Push testing closer to development through local testing, pairing, and strong automation practices.
Raise Team-Wide Testing Capability
- Promote habits that reduce defects and increase release confidence.
- Mentor less experienced team members, particularly in automation and test design.
- Continuously improve how the team approaches quality—not just how tests are written.
Requirements
- Significant experience in QA or software engineering with exposure to modern testing practices.
- Hands-on experience with Playwright, Cypress, or similar frameworks.
- Experience working in cross-functional teams practicing Continuous Delivery.
- Experience designing automated tests across multiple layers (unit, integration, API, acceptance).
- Strong ability to define meaningful test cases based on user behaviour and business logic.
- Comfortable reviewing changes for testability and risk without operating as a production-level engineer.
- Experience with microservice architectures and API-based systems.
- Familiarity with JavaScript/TypeScript and Python.
- Strong communication skills and a collaborative mindset.
- Experience improving QA practices and mentoring others.
- Experience leveraging AI-assisted development tools to improve test design and coverage.
Bonus requirements:
- Experience in private markets, financial technology, or data intelligence platforms.
- Experience working in Kubernetes-based environments.
What Success Looks Like After 3 Months
- E2E tests provide fast, clear confidence on critical workflows.
- Data issues are detected earlier through stronger validation and automated checks.
- Developers and QA collaborate closely with fewer late-stage surprises.
- Junior team members grow in automation confidence and capability.
- Defects are identified on the day they are introduced.
- Product quality is stronger and more consistent across services.
Our Tech Stack
- Playwright for E2E automation
- Python microservices architecture
- React and Next.js micro-frontends
- Kubernetes
