The Opportunity

The Analytics team is a critical engine driving 9fin's mission, and our data platform sits at its core. We are strong believers in building robust, reliable data foundations to empower data-driven decisions across the entire business. The Analytics Engineering team is responsible for designing, building, and maintaining our central data warehouse, creating the foundational data models that underpin analytics, reporting, and operational excellence across various departments, including Product, Finance, Operations, and more.

We are seeking a skilled Analytics Engineer to join us and elevate 9fin's data capabilities. In this role, you will focus on building and optimizing the core data warehouse, ensuring data quality, accessibility, and performance for a wide range of internal stakeholders. You will be instrumental in creating a trusted and well-governed data environment that enables informed decision-making at all levels of the organization. This is an opportunity to shape the very foundation of how 9fin leverages data for both strategic insights and operational efficiency.

What you'll work on

Every day is different but a key contributor to our data platform, you might:

• Lead the Design and Evolution of dbt Models: Designing, building and refactoring robust staging, intermediate and mart layer models within BigQuery and dbt, ensuring they are scalable, well-tested and capable of supporting complex product, commercial and operational analytics use cases across the business.
• Drive Metric Definition and Semantic Consistency: Owning the evolution of key business and product metrics, refining the semantic layer to ensure consistent KPI definitions across tools, and reducing ambiguity or duplication in how core metrics are calculated and consumed.
• Strengthen End-to-End Data Flows: Partnering closely with Data Engineering to improve ingestion and transformation reliability, validating cross-system data movement, and proactively identifying and resolving structural weaknesses in ELT pipelines.
• Integrate New Business Domains into the Warehouse: Scoping and implementing changes to data models as new systems, teams or initiatives are introduced, ensuring they are cleanly and sustainably integrated into our warehouse architecture.
• Lead Complex Data Investigations: Tracing high-impact data issues from dashboards back to source systems, identifying root causes, and implementing durable, long-term fixes that improve overall platform reliability and trust.
• Collaborate and Enable Decision-Making: Working directly with senior stakeholders across Product, Finance, Commercial and Operations to translate ambiguous business problems into well-structured, production-ready data models that enable confident, data-driven decisions.
• Raise the Bar for Analytics Engineering: Contributing to modelling standards, testing frameworks and documentation practices, reviewing peer work, and mentoring mid-level engineers to continuously improve how we build and operate our data platform.

About You

This role will be a great fit if you:

• Have strong data warehousing fundamentals: You understand dimensional modelling and modern warehouse design principles, and you’ve applied them in production environments to build scalable, maintainable data models

• Bring significant hands-on experience with dbt and cloud warehouses: You’ve designed and refactored complex staging, intermediate and mart-layer models in platforms such as BigQuery or Snowflake, and you optimise for clarity, performance and long-term maintainability.

• Demonstrate deep SQL expertise: You are highly fluent in SQL, comfortable with complex transformations, window functions and performance optimisation, and able to reason clearly about query plans and trade-offs.

• Have strong experience with semantic and BI layers: You have worked extensively with modern semantic or BI platforms (e.g. Omni, Cube or similar), understand how metric definitions propagate across tools, and have owned the design and maintenance of consistent, reliable KPI logic powering self-serve analytics.

• Understand ELT and pipeline mechanics: You are comfortable working within modern ELT architectures, collaborating with Data Engineering on ingestion and orchestration, and troubleshooting issues that span from source systems to downstream models.

• Have strong metric judgment: You’ve worked on defining and evolving core business or product metrics, understand the importance of semantic consistency, and know how to reduce ambiguity in KPI definitions across teams and tools.

• Care deeply about data quality: You implement robust testing in dbt, proactively identify weak points in modelling logic, and prioritise clean, well-documented, production-ready data assets over quick fixes.

• Are comfortable operating in ambiguity: You can take loosely defined business problems, ask the right questions, and translate them into structured, reusable data models without heavy direction.

• Communicate clearly and influence effectively: You can articulate trade-offs, push back constructively when requirements are unclear or fragile, and build strong working relationships across Product, Finance, Commercial and Operations teams.

• Operate with an AI-native mindset: You actively use AI tools to increase your leverage; accelerating SQL development, generating and refining dbt tests and documentation, automating repetitive workflows, and continuously experimenting with ways to improve productivity. You treat AI as a force multiplier in your daily work, not an afterthought.

• Bonus points if you are:

  • Experienced with orchestration tools such as Dagster or Airflow
  • Proficient in Python for automation or tooling around the warehouse

A note from the hiring manager

At 9fin, data isn’t just a support function; it’s at the core of our product. You’ll be surrounded by smart, curious people who are passionate about using data to make better decisions, improve our product, and create meaningful impact. If you’re looking for autonomy to own high-impact initiatives from conception through to delivery, and the opportunity to influence the entire organisation, then 9fin might be the perfect fit for you. I’d love to hear from you, apply now to learn more! – Rory, Analytics Engineering Manager

Our benefits

We’re a scaling start up, and we enjoy sharing our success, when the company succeeds, we always reinvest that in our people. We also offer huge amounts of responsibility, an abundance of opportunity for growth and a platform to truly excel.

Financial & Insurance

• Competitive Salary (our salary bands are benchmarked at the top end of the market)
• Equity options
• Pension (your minimum contributions are 4% with 9fin matching up to 7%)
• Private Medical Insurance
• Paid sick leave with Income Protection for long periods of illness
• Group Life Assurance
• Season Ticket Loan & Cycle to Work schemes

Time off

• 25 holiday days per year
• Local public holidays (with the ability to exchange them for alternative days)
• Hybrid working model, to allow you the flexibility to decide how, where and when you do your best work
• Work abroad for up to 3 months a year
• 1 month paid sabbatical after 5 years of service
• Enhanced parental leave & flexible working arrangements available

Training & Culture

• Professional learning and development budget
• Quarterly team socials
• Summer and Winter company social events

9fin is an equal opportunities employer

At 9fin we are dedicated to building and promoting a fair and inclusive workplace where everyone can reach their full potential and truly belong. We recognize that building diverse teams enables a more creative and productive environment. If you’re excited about this role but your experience doesn’t perfectly align with the job description, we encourage you to apply anyway. You might just be who we’re looking for — either for this role, or perhaps another.