Collaborate with product engineers to understand event data schemas and translating raw event streams into data models within the data warehouse to create a single source of truth for key metrics.
Build well-governed dbt models in Snowflake, including the development of the core data warehouse, data marts, metrics, and reusable datasets.
Apply dimensional modeling to ensure clear relationships and performant joins, while strategically utilising OBT (One Big Table) designs to optimise for BI tool performance and ease of end-user access.
Evolve the semantic layer within Looker to define governed, maintainable approaches to metrics.
Design and implement robust testing, monitoring, and alerting frameworks for analytics data to proactively identify and resolve pipeline failures.
Contribute to building a high level of data integrity across the dbt transformation layer, ensuring that SQL logic is robust, maintainable, and accurate.
Help drive the adoption of self-serve analytics through clear technical documentation, training sessions, and enablement strategies for non-technical users.
Create high-quality datasets specifically structured to serve as the reliable context for AI agents, ensuring our data models are optimised for automated discovery and LLM-driven productivity.
Partnering with Finance, Sales and Compliance teams to translate requirements into governed data models that ensure financial datasets remain audit-ready and fully reconciled.

Expert-level SQL skills to write robust, maintainable, and highly performant code using Snowflake.
Proven experience building and scaling data pipelines using dbt. Including incremental loading patterns, macros, and the handling of late-arriving data.
Experience developing complex semantic layers in Looker.
Practical experience handling data from event-driven systems to capture state-changes over time.
Expertise in Dimensional Modeling (Star Schemas) and OBT (One Big Table) design patterns to balance warehouse performance with end-user accessibility.
A rigorous approach to data quality, comprehensive audit logging and reconciliation frameworks to ensure every record can be fully reconciled against source systems for Finance and Compliance audits.
Proven experience managing the data warehouse lifecycle, including implementing Slowly Changing Dimensions (SCDs) and schema evolution strategies to ensure historical accuracy and long-term data lineage.
A natural analytical, numerical mindset and ability to translate complex data problems into clear findings for both technical and non-technical stakeholders.
A strong willingness to work independently, take initiative, and take full ownership of the data transformation layer and key business metrics.

Finance, Insurance, or FinTech Background: Experience working in a financial environment like Finance or Insurance where high precision of data is important.

Hybrid

Super Payments is hiring a Senior Analytics Engineer