Senior Analytics Engineer

We are seeking an experienced Senior Analytics Engineer to join our growing Data function at a pivotal stage of platform maturity.

This role is central to shaping the next phase of our analytics ecosystem - designing scalable, high-quality decision-making data models, strengthening governance and reliability, and enabling insight-driven decision-making across Product, Risk, Finance, and Commercial teams.

You will operate at the intersection of modelling architecture, workflow reliability, and technical standards, working closely with Data Analysts, Data Engineering, Data Science, Software Engineering, and senior business stakeholders.

This is a hands-on senior individual contributor role with meaningful influence over our data architecture and engineering culture.

If you are excited by building clean, scalable analytics systems in a fast-moving fintech environment - and want real ownership rather than narrow ticket execution - this role is for you.

• Own modelling architecture for one or more business domains, ensuring scalability, clarity, and long-term maintainability

• Design, build, and evolve high-quality dbt models and analytics-ready data marts

• Translate complex business and product requirements into robust, well-documented transformation logic

• Establish and enforce modelling standards, naming conventions, and domain boundaries

• Drive Snowflake performance optimisation and cost governance initiatives

• Lead structured refactoring initiatives to reduce technical debt and improve maintainability

• Design and maintain Airflow DAGs and alerting frameworks (Dag Factory) to ensure reliable data workflows

• Own operational reliability for analytics pipelines, including incident response and SLA adherence

• Improve orchestration patterns, documentation standards, and monitoring practices

• Collaborate with Data Engineering to maintain clear separation between infrastructure ownership and analytics layer responsibilities

• Contribute to secure data access design and role-based access control (RBAC) frameworks

• Improve and maintain CI/CD processes for analytics workflows, ensuring safe and automated deployments

• Implement automated linting, testing, and code review standards to elevate engineering quality

• Strengthen lineage, documentation, and semantic governance across dbt and BI tooling

• Partner with stakeholders to ensure data definitions are consistent, trusted, and audit-ready

• Provide senior technical leadership through structured code reviews, peer learning sessions, and documentation practices

• Mentor Analytics Engineers and Analysts transitioning into engineering-focused roles

• Act as a modelling and data architecture subject matter expert within the organisation

• Champion best practices in SQL, dbt, version control, and scalable analytics design

• Partner on strategic initiatives across Product, Risk, and Finance analytics infrastructure

• Ensure analytics considerations are embedded early in architectural decisions

• Influence how new systems integrate into the broader data platform

• 4+ years in Analytics Engineering, Data Engineering, or advanced Analytics roles

• Strong expertise in SQL and modern data modelling principles

• Strong expertise in dbt and advanced dbt concepts

• Strong experience working with Snowflake (or comparable cloud data warehouse)

• Experience building and maintaining orchestration workflows

• Solid understanding of CI/CD, Git-based workflows, and version-controlled deployments

• Experience designing secure data access models and governance controls

• Ability to communicate clearly with technical and non-technical stakeholders

• Experience in fintech, payments, lending, or regulated environments

• Exposure to experimentation frameworks and product analytics ecosystems

• Experience driving cost optimisation in Snowflake environments

• Familiarity with Looker or other semantic BI layers

• Experience collaborating with Data Science teams to enable ML workflows

• Clearly defined data marts with trusted definitions

• Reduced technical debt and improved modelling consistency

• Measurable Snowflake cost efficiency improvements

• Fewer pipeline incidents and improved operational reliability

• Strong documentation and peer-reviewed engineering culture

• Trusted partnership with Product, Risk, and Finance teams

• Shape the analytics foundation of a scaling fintech platform

• Influence architectural decisions rather than simply implementing tickets

• Work on commercially critical systems at the core of the business

• Join a team that values engineering quality, ownership, and clarity