About the role
We are looking for a hands-on technologist with strong experience in large-scale data and asset modelling using Python, with particular expertise in Pydantic-based data modelling, schema definition and validation. Experience with AI-assisted development and agent orchestration tools is highly desirable, particularly where these technologies are used to accelerate high-quality software delivery.
In this role, you will work closely with data governance, architecture, technology, risk, compliance and business teams to translate complex regulatory, metadata and technology requirements into robust data models, reusable design patterns and platform-ready solutions.
- 5–6+ years of recent, hands-on Python development, including ownership of production services, reusable libraries and automation—not only scripts, notebooks or data analysis.
- Practical FastAPI and Pydantic experience covering API creation, schema design, complex validation, serialization, async processing, error handling and testing.
- Strong conceptual, logical, physical and metadata modelling, including canonical models, data contracts, source-to-target mapping, schema versioning, lineage and data quality.
- Experience processing large JSON, YAML and SQL datasets, with practical knowledge of batching, retries, idempotency, caching and performance optimisation.
- Strong production engineering practices: PyTest, Git, code reviews, CI/CD, deployment, monitoring and production support.
- A hands-on go-getter who can contribute from day one, work independently and deliver production-ready solutions quickly. Financial-services or regulated-domain experience is preferred
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