Analytics Engineer

About 9fin

9fin is the AI platform powering global debt markets — the world’s largest asset class at over $145 trillion.

Debt markets are vast, global, and mission-critical, yet still run on fragmented data, PDFs, and manual workflows. 9fin replaces this broken infrastructure with a single platform that centralises proprietary credit data, deep analysis, and high-value workflows across global markets.

Today, 9fin powers teams at 300+ blue-chip institutions worldwide, including global banks, asset managers, private equity firms, law firms, and advisors. The business is scaling at exceptional speed, with rapid expansion in the US and best-in-class retention driven by deep workflow adoption.

We’re at a defining inflection point. With proven product-market fit and strong, global market pull, 9fin is accelerating toward becoming the category-defining platform for debt markets worldwide.

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 Big Query 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.

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…