Python Engineer / Data Modeller

Our client, a consultancy supporting a leading global financial services organisation, is looking for a hands-on Data Modelling Specialist/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, alongside hands-on Collibra metadata management expertise. Experience in data modelling, governance, APIs, SQL and financial services would be particularly relevant. You will work closely with data governance, architecture, technology, risk and compliance teams, turning complex regulatory and metadata requirements into robust models and platform-ready solutions.

What You’ll Do · Design, enhance and maintain asset models within a leading metadata management platform, configuring asset types, relations, attributes, domains and workflows. · Develop high-quality Python solutions for data modelling and governance use cases, using 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 ten years’ professional experience, including practical delivery using Pydantic and FastAPI for data modelling, validation, schema design and API development, alongside JSON, YAML, REST APIs and SQL. · Strong hands-on experience with Collibra, including asset model and metamodel design, platform configuration and governance operating models. · Experience with metadata modelling, data taxonomies, lineage, data quality, business glossaries and governance workflow design. · Experience within financial services, ideally in risk, compliance, regulatory reporting or technology risk environments, with exposure to large-scale financial data. · 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.

Good to Have · Understanding of financial services regulatory frameworks such as BCBS 239, GDPR, DORA, MiFID or Solvency II, and how they influence governance and controls. · Experience with Collibra APIs, workflow development or Edge/Connect integrations. · Experience integrating metadata platforms with data platforms such as Snowflake, Databricks, Azure, AWS or Informatica. · Knowledge of data mesh, data products or domain-driven design concepts. · Data governance, data management or cloud certifications.