Data Architect (UK)
A hands-on Data Architect owning the architecture of Quantios Insights, a multi-tenant analytics platform built on Azure Databricks, Unity Catalog, SQL, Python, and dbt. The role defines lakehouse models, integration and governance patterns for regulated financial services customers, and feeds high-quality datasets into RAG/LLM AI pipelines.
- Compensation
- Not disclosed
- Location
- Fleet, United Kingdom
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Architecture
- Posted
Skills
Must have
- Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, Information Systems, or related field; or equivalent experience
- 7+ years in data engineering, data architecture, or platform architecture
- At least 3 years hands-on Azure Databricks in production
- Production experience with Unity Catalog (catalogs/schemas as isolation boundaries, grants, row filters, column masks, service principals, lineage, system tables)
- Hands-on experience implementing fine-grained access control (ABAC or equivalent) on Databricks or comparable platform
- Strong working experience with dbt (ideally dbt-databricks), including incremental models, testing, and multi-environment deployment
- Experience with Terraform (including Databricks provider) and Databricks Asset Bundles or equivalent IaC within CI/CD pipelines
- Strong SQL and Python used routinely in current work
- Deep experience with medallion architecture, dimensional modelling, and semantic layer design
- Experience designing platforms for regulated environments, with working knowledge of data residency, encryption, private networking, and audit requirements
- Strong communication skills, with the ability to explain architectural trade-offs to engineers, product owners, and customer security teams
Nice to have
- Experience designing or operating a multi-tenant data platform
- CI/CD experience, Azure DevOps preferred
Full description
Quantios is a leading provider of software solutions for the trust administration and corporate services industry. With over 30 years of experience, we empower our clients with innovative technology that enhances governance, operations, and investment on a global scale. At Quantios, we are committed to fostering a diverse and inclusive workplace where creativity, learning, and collaboration drive success.
As a Data Architect at Quantios, you will own the architecture of Quantios Insights, our multi-tenant analytics platform. Built on Azure Databricks and Unity Catalog, Insights unifies data from all Quantios products and powers analytics, regulatory insights, MCP-based data access, and AI-driven capabilities for regulated financial services customers.
You will define the architectural standards, models, integration patterns, and governance frameworks that keep the platform reliable, scalable, secure, and demonstrably isolated between customers. This is a hands-on role: you will set the standard through working code and documented patterns, using SQL, Python, and dbt in your daily work.
This role also plays a central part in the internal AI Enablement Centre of Excellence, ensuring high-quality datasets flow into RAG pipelines, LLM evaluation frameworks, and strategic AI initiatives across the business. You will collaborate closely with Data Engineers, LLMOps Engineers, Product Owners, Portfolio Architects, and engineering teams to shape Quantios’ data and AI ecosystem.
Job Responsibilities:
- Enterprise Data Architecture & Strategy
- Define the architectural vision, principles, and standards for Quantios’ enterprise data platform aligned to the business and product strategy.
- Own and evolve the data architecture for Quantios Insights, including data ingestion patterns, lakehouse design, semantic modelling, and analytical layers.
- Define architectural guardrails and reference patterns for Databricks to support customer deployment flexibility.
- Contribute to the long-term roadmap for data and AI capabilities across Quantios products and internal teams.
- Hands-On Delivery & Technical Leadership
- Use SQL, Python, and dbt hands-on: build reference implementations, review and write pull requests, and unblock Data Engineers directly.
- Set the standard through working code and documented patterns (architecture decision records, runbooks, reference models), not only diagrams.
- Review and challenge work from engineering teams and external delivery partners, confirming that what is documented matches what is built and running.
- Work closely with Portfolio Architects to align product architecture, data architecture, and platform strategy.
- Collaborate with Product Owners to translate analytical and AI requirements into data architectural designs.