Senior Analytics Engineer

Data Pipelines & Modeling

• Upstream Engineering Collaboration: 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.
• Maintainable Data Pipelines: Build well-governed dbt models in Snowflake, including the development of the core data warehouse, data marts, metrics, and reusable datasets.
• Data Modeling: 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.

Governance & Reliability

• Semantic Layer Ownership: Evolve the semantic layer within Looker to define governed, maintainable approaches to metrics.
• Quality Frameworks: Design and implement robust testing, monitoring, and alerting frameworks for analytics data to proactively identify and resolve pipeline failures.
• Data Quality Governance: Contribute to building a high level of data integrity across the dbt transformation layer, ensuring that SQL logic is robust, maintainable, and accurate.

Self Serve & Collaboration

• Self-Serve Strategy: Help drive the adoption of self-serve analytics through clear technical documentation, training sessions, and enablement strategies for non-technical users.
• AI Readiness: 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.
• Stakeholder Collaboration: Partnering with Finance, Sales and Compliance teams to translate requirements into governed data models that ensure financial datasets remain audit-ready and fully reconciled., * SQL & Warehouse Engineering: Expert-level SQL skills to write robust, maintainable, and highly performant code using Snowflake., * Data Modeling: Expertise in Dimensional Modeling (Star Schemas) and OBT (One Big Table) design patterns to balance warehouse performance with end-user accessibility.
• Data Integrity & Governance: 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.
• Warehouse Evolution & Historical Tracking: 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.

• Modern Transformation Frameworks: Proven experience building and scaling data pipelines using dbt. Including incremental loading patterns, macros, and the handling of late-arriving data.
• Semantic Layer & BI: Experience developing complex semantic layers in Looker.
• Event-Driven & Time-Series Data Modeling: Practical experience handling data from event-driven systems to capture state-changes over time., * Finance, Insurance, or FinTech Background: Experience working in a financial environment like Finance or Insurance where high precision of data is important.
• Technical Communication: A natural analytical, numerical mindset and ability to translate complex data problems into clear findings for both technical and non-technical stakeholders.
• Ownership & Initiative: A strong willingness to work independently, take initiative, and take full ownership of the data transformation layer and key business metrics.

*The stated experience and background is a guide and does not preclude applications from candidates with more or less experience, provided the requisite skills can be demonstrated.

Our Benefits - here’s a few and more to come ….

• Tax advantage Share Options
• Flexible working model
• Work from home set up
• Learning & Development opportunities
• Contributory Pension Scheme
• Free Team lunch (Tues & Thurs) and social evenings
• Comprehensive PMI & x4 Life Insurance
• Your birthday off, plus one Revival day

Super Payments is the only global fintech platform providing 0% processing fees for merchants. Our mission is to use data and AI to make payments free for businesses, so that everyone wins.

At Super, we are disrupting payments, like Spotify did to music and Robinhood did to trading. We don’t make money from transaction fees; instead, we monetise through value-added services such as lender commissions and FX. Our platform supports multiple payment methods - from traditional cards to direct bank transfers via open banking, as well as Apple Pay, Google Pay, and our own Buy Now Pay Later solution.

Super has raised $66M from leading investors including Accel, Union Square Ventures and Local Globe (the same investors behind Spotify, Stripe, Monzo) and founded by Samir Desai CBE, co-founder of Funding Circle.

Already trusted by thousands of businesses and more than 4 million customers, Super is processing at a run rate of £1.5B and growing 4x YOY

Our Values

• Customer obsessed: We only succeed when our customers do.
• Move fast: Build, test and improve quickly. Progress matters more than perfection.
• Own it: Be accountable, solve problems, and make it happen.
• Be open: Act with honesty and respect. Transparency builds trust.
• Win together: Collaboration beats ego every time., We are using modern data technologies to build an AI enabled data analytics platform. One that facilitates fast and iterative data analysis, allowing you to get on with asking questions of the data and uncovering insights. Snowflake SQL analytics pipelines are created in dbt, Looker is the data visualisation platform to provide a maintainable and consistent way to define metrics and dashboards. Python is the go-to language for statistical analysis and data engineering.