We are looking for an adaptable and highly motivated individual with a diverse technical skillset to work in a fast-paced Data Warehouse Engineer role within a new Enterprise Data Intelligence team within the technology function. This is a unique opportunity within our industry to work on a greenfield project building a new corporate data warehouse, which will serve as the basis for all enterprise reporting within BAM.
This is a high visibility and high impact opportunity given the diverse and cross functional stakeholders mandate. As such, the ideal candidate will be highly adaptable and willing to learn new technical skills as well as become a partner with our business and support a Centre of Excellence as we build out a self-service BI function.
We work on a modern and evolving data platform built on Snowflake, DBT, Airflow (Astronomer), FiveTran, Sigma Computing and PowerBI. The team includes Analytics Engineers, Applied AI Engineers, and DevOps Engineers — this role works closely with all three disciplines, with Analytics Engineers as the primary day-to-day collaborators on data modelling, and DevOps owning infrastructure provisioning and Terraform.
Responsibilities
• Building data analysis pipelines and frameworks for business-critical systems.
• Creating automated data quality and delivery solutions that can run without engineer intervention.
• Work on data governance frameworks and auditing to ensure data security.
• Optimize data warehouse workloads for both cost and performance.
• Create training documentation that will be used by other teams.
• Data modelling for the semantic layer, producing clean, well-structured datasets that are ready for self-service consumption.
• Supporting a large self-service BI user population — acting as a first point of contact for data questions, troubleshooting report issues, and enabling users to get value from the platform independently.
• Working with our Claude Code agent framework as a primary development tool, contributing to and extending domain agents for dbt and data pipeline work. Candidates with experience using AI coding tools to accelerate data engineering work will be given priority — this is a genuine differentiator in how we build.
Qualifications
• Demonstrable experience working with complex data sets, preferably with prior experience in a financial setting.
• Strong analysis skills to extract requirements from end users rather than work from a fixed spec.
• Excellent data modelling capability, particularly for semantic layer and self-service consumption.
• A focus on automation and developing solutions that don't need hands-on work to repeat.
• The ability to provide clarity and insight through compelling data visualisation — you will encounter BI tools and be expected to collaborate on report delivery, though this is not the core focus of the role.
• A focus on data quality.
• Demonstrable expertise in Snowflake with at least 5 years of experience.
• Production deployments of DBT and at least 3 years of experience.
• Strong Python skills for data pipeline and transformation work.
• Additional technologies that will be encountered during the job, with support and training given on technologies you haven't worked on:
o FiveTran / HVR
o Airflow
o Sigma Computing
o Power BI
o Terraform (infrastructure is owned by DevOps; this role will read and collaborate on Terraform config but is not expected to own it)
Even if your experience doesn’t match every requirement, we’d still love to hear from you—if you’re excited about this role, we encourage you to apply!