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# Python Engineer - Data Modelling

- **Company:** Robert Walters
- **Location:** Glasgow, UK
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software Quality, Databases, Continuous Integration, Data Architecture, Data Integrity, Serialization, Enterprise Information Management, JSON, Python (Programming Language), SQL Databases, Systems Integration, Unstructured Data, YAML, Data Ingestion, Git, Fastapi, Restful APIs
- **Published:** August 7, 2026
- **Apply:** https://www.careerboard.com/pt/en/find-jobs-in-United-Kingdom/-A6F311EE96DFF283C5/

## About the Role

* Strong Python skills, with experience in Pydantic, FastAPI, JSON, YAML, REST APIs and SQL.
 * Experience with metadata modelling, data quality, lineage, business glossaries and governance workflows.
 * Experience in financial services, ideally in banking, risk, compliance, regulatory reporting, cyber, fraud or technology risk.
 * Knowledge of data architecture, enterprise information management and Git-based development, testing, documentation and CI/CD.
 * Experience using AI-assisted development tools, with the ability to review and refine generated outputs.
 * Strong analytical, communication and stakeholder management skills, with high attention to detail and the ability to work in a fast-paced environment.

## Description

* Develop robust Python solutions for data modelling and governance, using Pydantic for schema definition, validation, serialisation, configuration-driven models and API-ready structures.
 * Build reusable Python libraries, modelling components and automation frameworks to support data ingestion, governance workflows, data quality, lineage, integrations and reporting at enterprise scale.
 * Design solutions for the processing and governance of large-scale financial and risk data sets, with a focus on performance, data integrity, traceability and regulatory control.
 * Work with APIs, JSON, YAML, SQL and both structured and unstructured data formats, using in-memory databases or caching technologies to support efficient integrations, validation workflows and governance automation.
 * Use AI-assisted coding tools responsibly to improve Python development productivity, code quality, documentation, testing and solution design, while reviewing all outputs for security, compliance, accuracy and maintainability.


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