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Synechron

Data Modeler

Glasgow
Posted about 15 hours ago
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Experienced Data Modeler – Collibra & Python

We are looking for an experienced and motivated Data Modeler – Collibra & Python to support enterprise data modelling, metadata management, and data governance initiatives within a complex financial-services environment.

The successful candidate will combine strong Python development skills with hands-on experience in Collibra, metadata modelling, data governance, data lineage, data quality, and regulatory data management.

Job Description

As a Sr. Data Modeler Engineer, you will design, enhance, and maintain enterprise asset models and governance solutions while developing reusable Python services and automation components to support data ingestion, governance workflows, integrations, validation, lineage, and reporting.

Responsibilities

  • Design, enhance, and maintain asset models in Collibra aligned with enterprise data governance, metadata management, regulatory, and technology-risk requirements.
  • Define and configure Collibra asset types, relations, attributes, communities, domains, responsibilities, workflows, roles, and operating models.
  • Develop high-quality Python solutions for data modelling and governance use cases.
  • Use Pydantic for schema definition, validation, serialization, configuration-driven models, and API-ready data structures.
  • Develop reusable Python libraries, modelling components, and automation patterns for data ingestion, governance workflows, data quality, lineage, integrations, and reporting.
  • Design solutions to process and govern large-scale financial and risk data sets, with a focus on performance, data integrity, traceability, and regulatory controls.
  • Build and support integrations using APIs, JSON, YAML, SQL, and structured or unstructured data formats.
  • Use in-memory databases or caching technologies to support performant integrations, validation workflows, and governance automation.
  • Support Collibra APIs, workflow development, import/export tooling, Edge/Connect integrations, and related integration patterns.
  • Collaborate with data architects, engineers, data stewards, business stakeholders, risk teams, compliance teams, and technology-control functions.
  • Use AI-assisted development tools responsibly to improve development productivity, testing, documentation, and solution design.
  • Review all AI-generated outputs for security, compliance, accuracy, maintainability, and production readiness.
  • Maintain technical documentation, data models, governance procedures, code documentation, and operating guidelines.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Required Skills & Experience

  • Bachelor’s degree in Computer Science, Information Technology, Data Management, Engineering, or a related discipline.
  • Strong professional experience in Python development for data modelling, governance, data engineering, or enterprise integration use cases.
  • Hands-on experience with Collibra or a comparable metadata management and data governance platform.
  • Experience designing and configuring Collibra asset models, metamodels, workflows, roles, responsibilities, domains, communities, and operating models.
  • Strong knowledge of metadata modelling, logical data modelling, data taxonomies, data lineage, data quality, business glossaries, data catalogues, critical data elements, and governance workflows.
  • Practical experience with Pydantic for schema definition, validation, serialization, and configuration-driven models.
  • Experience with FastAPI, REST APIs, JSON, YAML, SQL, and service integration.
  • Experience building reusable Python libraries, automation tools, governance workflows, and data integration components.
  • Understanding of data architecture, enterprise information management, regulated data lifecycles, and modern engineering practices.
  • Experience with Git-based development, code review, automated testing, documentation, and CI/CD concepts.
  • Strong analytical, problem-solving, communication, documentation, and stakeholder-management skills.
  • Experience working with large-scale financial, risk, regulatory, compliance, cyber, fraud, or technology-risk data.

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Preferred Skills

  • Experience with Collibra APIs, workflow development, import/export tooling, Edge, Connect, or similar integration technologies.
  • Experience integrating Collibra with Snowflake, Databricks, Azure, AWS, GCP, Informatica, data-quality tools, or enterprise data platforms.
  • Knowledge of data mesh, data products, domain-driven design, enterprise data marketplaces, and data ingestion pipelines.
  • Experience using AI-assisted development tools such as GitHub Copilot, ChatGPT, Claude, Cursor, or similar.
  • Familiarity with financial-services standards and regulations such as BCBS 239, GDPR, CCPA/CPRA, DORA, MiFID, Basel, or Solvency II.
  • Knowledge of data governance, data management, cloud, or related professional certifications.
  • Experience with caching technologies, in-memory databases, SQLAlchemy, Pytest, or asynchronous Python development.

What You’ll Bring

  • A strong combination of data governance, metadata management, and software engineering expertise.
  • The ability to translate governance and regulatory requirements into practical, reusable technical solutions.
  • Strong attention to data quality, traceability, control effectiveness, and documentation.
  • A collaborative approach to working with business, technology, risk, compliance, and control stakeholders.
  • A responsible and security-conscious approach to AI-assisted software development.
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Location

Glasgow, Scotland, United Kingdom

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