Data Modeler

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.

• Design, enhance and maintain enterprise asset models in Collibra, aligned with data governance, metadata management, regulatory and technology risk requirements.
• Define and configure Collibra asset types, relationships, attributes, communities, domains, responsibilities, workflows, roles and operating models.
• Develop high-quality Python solutions for data modelling and governance use cases, using Pydantic for schema definition, validation, serialization, configuration-driven models and API-ready data structures.
• Build reusable Python libraries, modelling components and automation patterns supporting data ingestion, governance workflows, data quality, lineage, integrations and reporting at enterprise scale.
• Design solutions for processing and governing large-scale financial, risk and enterprise data sets, with a strong focus on performance, data integrity, traceability and regulatory controls.
• Work with APIs, JSON, YAML, SQL and structured/unstructured data formats.
• Leverage in-memory databases and caching technologies where appropriate to support high-performance integrations, validation workflows and governance automation.
• Use AI-assisted coding and development tools responsibly to improve development productivity, code quality, documentation, testing and solution design.
• Review, validate and refine AI-generated outputs to ensure they meet required standards for security, compliance, accuracy, maintainability and production readiness.
• Collaborate with technical and non-technical stakeholders to translate complex data and regulatory requirements into practical technology solutions.

• Strong Python development experience with practical expertise in Pydantic and FastAPI for data modelling, validation, schema design, serialization, API development and service integration.
• Strong understanding of JSON, YAML, REST APIs and SQL.
• Hands-on experience with Collibra or similar metadata management platforms, including asset model/metamodel design, platform configuration, governance operating models and stewardship structures.
• Experience with metadata modelling, logical data modelling, data taxonomies, lineage, data quality, business glossaries, data catalogues, critical data elements and governance workflows.
• Experience with in financial services, ideally across banking, risk, compliance, regulatory reporting, cyber, fraud or technology risk environments.
• Experience working with large-scale financial or enterprise data.
• Knowledge of data architecture, enterprise information management and regulated data life cycles.
• Strong understanding of modern engineering practices including Git-based development, code reviews, automated testing, documentation and CI/CD.
• Experience using AI-assisted development tools such as Git Hub Copilot, ChatGPT, Claude, Cursor or similar technologies, with the ability to validate, refine and product ionise AI-generated solutions responsibly.
• Strong analytical and problem-solving skills with the ability to work through complex data and technical challenges.
• Excellent communication, documentation and stakeholder management skills, with the ability to influence across business, technology and control functions.
• High attention to detail, strong ownership and the ability to thrive in a fast-paced environment.
• Ability to deliver clear, reusable, scalable and governable technology solutions.

• Understanding of financial services regulatory and industry frameworks such as BCBS 239, GDPR, CCPA, DORA, MiFID, Basel, Solvency II or equivalent standards.
• Understanding of how regulatory requirements influence data governance, traceability, controls and data management design.
• Experience with Collibra APIs, workflow development, import/export tooling, Edge/Connect integrations or similar integration patterns.
• Experience integrating Collibra with enterprise data platforms such as Snowflake, Databricks, Azure, AWS, GCP, Informatica or data quality platforms.
• Knowledge of data mesh, data products, domain-driven design, enterprise data marketplaces and data ingestion pipelines.
• Data governance, data management, cloud or related professional certifications.