Senior Data Architect (8-month FTC)

I'm hiring a Senior BI Data Architect to join a global SaaS organisation and take ownership of a large-scale data platform transformation.

This is a hands-on architecture role sitting at the intersection of data engineering and BI - where your work will directly shape how the business uses data to make decisions.

The company A global technology business operating in the data and insights / research space, serving major clients worldwide and processing hundreds of millions of data points annually.

They are investing heavily in modernising their data platform and analytics capabilities, with a strong focus on performance, scalability, and self-serve analytics.

The role You'll take full ownership of the Databricks Lakehouse and BI architecture, leading the migration away from legacy systems while building a clean, governed and scalable platform.

This is not just a design role - you'll be deep in the detail, refactoring SQL, building pipelines, and optimising performance.

What you'll be doing • Design and implement a governed Databricks Lakehouse architecture (Unity Catalog, schemas, volumes)

• Lead migration of complex legacy SQL logic into modular, scalable pipelines


• Build and optimise data transformation frameworks using Spark / Python / SQL pipelines


• Act as the go-to expert for query performance optimisation (Spark execution plans, data skew, joins)


• Design and implement dimensional data models (star / snowflake schemas)


• Architect the semantic layer for BI (Omni or similar tools like Looker)


• Build CI/CD pipelines to automate testing and deployment


• Work with stakeholders across Product, Finance, and Commercial teams to deliver scalable solutions

What you bringMust-haves • 8+ years in data engineering / data architecture

• Deep experience with Databricks (Lakehouse, Delta Lake, Unity Catalog)


• Expert SQL and distributed computing knowledge


• Strong experience with data modelling (star / snowflake schemas)


• Proven experience migrating legacy data platforms


• Ability to optimise performance across large datasets


• Experience with modern BI semantic layers (e.g. Looker, Omni, Superset)


• Experience with CI/CD and version control (Git)

Nice to have • Experience with dbt or similar transformation frameworks

• Exposure to AI/BI or natural language querying tools


• Experience in multi-tenant or embedded analytics environments

Why this role • Own and shape a modern data platform at scale

• High-impact project with visible business outcomes


• Combination of architecture + hands-on engineering


• Work on performance, scalability, and governance challenges


• Flexible, remote-friendly working

What success looks like • A clean, governed Lakehouse architecture

• Improved performance and reduced cost across the platform


• Scalable, reusable data pipelines


• A robust semantic layer enabling self-serve analytics across the business

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