The Role
Build and maintain production-quality Python services and data pipelines for financial datasets, implement REST APIs, use SQL for analysis, deploy to cloud infrastructure with CI/CD, collaborate with product and research teams, and operationalise quantitative research into reproducible production workflows.
Summary Generated by Built In
We’re looking for a quantitative developer who is passionate about working with financial data and building products that traders and researchers actually use. At Intropic you’ll join a fast-moving fintech startup where engineers own hard, open-ended problems across research, data and product — we don’t just pick up JIRA tickets.
A typical week will mix Python and SQL development, deploying infrastructure changes, building new features for financial-data products, strategic planning with team leads, and attending client meetings to explain work and gather feedback. You should enjoy shipping production-grade code, be comfortable with ambiguity, collaborate closely with analysts and product teams, and take pride in clean, well-tested systems that power real trading and research workflows.
We hire the person, not the CV. If you thrive on end-to-end ownership and want to help shape product and research direction, we’d love to hear from you.This is a full-time role, expected to start in the first half of 2026.
Responsibilities
- Collaborate closely with product managers, research analysts and other engineers to define project scope, translate research into product requirements, and deliver concrete technical solutions.
- Maintain, extend and improve Intropic’s suite of financial-data products, from backend data services to client-facing features.
- Design, implement and ship clean, well-tested, production-ready Python code and reusable Python libraries used across the stack.
- Build and maintain data processing pipelines that ingest, transform and validate large and heterogeneous financial datasets.
- Build production REST APIs and data services, and use SQL to analyse large relational datasets.
- Deploy production-quality code to cloud infrastructure (cloud providers, CI/CD pipelines) and own the end-to-end release process.
- Work with analysts to operationalise quantitative research: production-wise models, automate experiments, and ensure reproducible results.
Qualifications - Required
- STEM graduate (or final-year student) with demonstrable coding ability.
- Strong Python skills (other OOP languages such as Java or C++ are welcome and seen as a plus).
- Practical experience with SQL and relational databases
- Comfortable with the command line and modern version-control workflows (example: GitHub / GitLab / Bitbucket).
- Strong communicator, able to explain technical work to both technical and non-technical audiences.
- Independent, self-driven learner who takes ownership and can work across disciplines.
- Familiarity with automated testing and general software engineering best practices (code review, CI concepts).
Qualifications - Preferable
- 0–2 years professional experience in a software engineering, quantitative developer, or data engineering role. Experience within the finance industry is a strong plus.
- Good working knowledge of NumPy and Pandas.
- Familiarity with backend development and async programming in Python / modern Python frameworks.
- Experience with containerisation and cloud deployments (Docker, cloud platforms such as AWS).
- Practical exposure to financial data via university projects, internships or full-time work.
Skills Required
- STEM graduate (or final-year student) with demonstrable coding ability
- Strong Python skills
- Practical experience with SQL and relational databases
- Comfortable with the command line and modern version-control workflows (GitHub / GitLab / Bitbucket)
- Strong communicator, able to explain technical work to technical and non-technical audiences
- Independent, self-driven learner who takes ownership and can work across disciplines
- Familiarity with automated testing and general software engineering best practices (code review, CI concepts)
- 0-2 years professional experience in software engineering, quantitative development, or data engineering
- Good working knowledge of NumPy and Pandas
- Familiarity with backend development and async programming in Python / modern Python frameworks
- Experience with containerisation and cloud deployments (Docker, AWS or other cloud platforms)
- Practical exposure to financial data via university projects, internships or full-time work
- Other OOP languages such as Java or C++ (welcome/plus)
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The Company
What We Do
Intropic is a fintech start-up that provides advanced financial intelligence and data processing tools for the capital markets industry. By combining agentic AI and elastic cloud infrastructure with deep market expertise, Intropic delivers high-impact data products, including index rebalance forecasts, which are utilized by leading financial institutions, hedge funds, and asset managers to effectively manage risk and optimize multi-billion dollar trading flows.
