Senior Analytics Engineer

Role Overview

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.

Key Responsibilities

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.

Requirements

We'd love it if you have

• SQL & Warehouse Engineering: Expert-level SQL skills to write robust, maintainable, and highly performant code using Snowflake.
• 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.

Modeling & Architecture

• 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.

Domain Knowledge & Ownership

• 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

If you are excited about sharing the adventure, joining a growing team with big ambitions and you are really great at what you do, then apply now!

Super Payments is an equal opportunity employer, embracing diversity in all its forms and fostering an inclusive environment. The company will not unlawfully discriminate on grounds of gender, sexual orientation, marital or civil partner status, gender reassignment, race, religion or belief, colour, nationality, ethnic or national origin, disability or age, neurodiversity status, pregnancy or trade union membership. 

Please let us know if you require any reasonable adjustments at any point during the application and/or recruitment process.