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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Analytics Engineer - **Company:** Super Payments - **Location:** London, UK (Remote available) - **Experience:** Expert - **Salary:** £77,290.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Audit Trail, BigTable, Data Governance, Data Integrity, Data Mart, Data Transformation, Data Warehousing, Software Design Patterns, Dimensional Modeling, Standard Sql, SQL Databases, Macros, Large Language Models, Snowflake, Data Layers, Core Data, Data Lineage, Looker Analytics, Data Pipelines - **Published:** August 7, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5830785271 ## About the Role * 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. ## Description 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. ## Related Videos - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) ## Related Articles - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Analyst Salary Germany](https://www.wearedevelopers.com/magazine/277-data-analyst-salary-germany) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)