Python Engineer / Data Modeller

Our client, a consultancy supporting a leading global financial services organisation, is looking for a hands-on Senior Python Developer to join their data governance function, sitting within a technology risk and controls team. We are looking for candidates with strong Python development experience, ideally including FastAPI, who can turn complex regulatory and metadata requirements into robust, platform-ready solutions. Data modelling experience would be a nice to have, not essential. What You’ll Do

• Develop high-quality Python solutions using FastAPI, with Pydantic for schema definition, validation, serialisation and API-ready data structures.
• Build reusable Python libraries and automation patterns supporting data ingestion, governance workflows, data quality, lineage and reporting at enterprise scale.
• Design solutions to process and govern large-scale financial and risk data sets, with attention to performance, data integrity and regulatory control requirements.
• Work with APIs, JSON, YAML and SQL, using AI-assisted coding tools responsibly to improve delivery, reviewing all outputs for security, compliance and maintainability.

• Strong Python development skills with a minimum of 7 years’ professional experience, including practical delivery using FastAPI and Pydantic for API development, schema design and validation, alongside JSON, YAML, REST APIs and SQL.
• Knowledge of data architecture and modern engineering practices including Git-based development, code review, automated testing and CI/CD concepts.
• Experience using AI-assisted development tools such as GitHub Copilot, ChatGPT, Claude or Cursor, with the ability to validate and productionise generated outputs responsibly.
• Financial services experience, ideally within a large banking or financial institution, in risk, compliance, regulatory reporting or technology risk environments.
• Based in Glasgow or wider Scotland, able to commit to three days per week on-site.
• Data governance, data management or cloud certifications.

Good to Have

• Experience with data modelling, metadata management, data taxonomies, lineage, data quality, business glossaries or governance workflow design.
• Understanding of financial services regulatory frameworks such as BCBS 239, GDPR, DORA, MiFID or Solvency II.
• Knowledge of data mesh, data products or domain-driven design concepts.