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 companyA 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 roleYou'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
- 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)
- Experience with dbt or similar transformation frameworks
- Exposure to AI/BI or natural language querying tools
- Experience in multi-tenant or embedded analytics environments
- 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
- 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