Head of Business Intelligence

Overview

is connecting the world to the future of finance. As the most trusted and fastest-growing global crypto company, it helps millions of people worldwide safely access cryptocurrency. Since its inception in 2011,  has earned the trust of over 90 million wallet holders and more than 40 million verified users, facilitating over $1 trillion in crypto transactions.

We are looking for a Head of Business Intelligence to lead our BI function and help scale reporting and decision-making across  This role is based in London and sits at the intersection of analytics, product, and business operations.

The Head of BI is a senior people leader responsible for building and managing a team of data analysts who own company-wide reporting. Your team will deliver high-quality dashboards, recurring reporting, executive insights, and self-serve analytics foundations that empower teams across Product, Growth, Trading, Fraud, Finance, and Operations.

You will partner closely with the Data Engineering team who build and maintain pipelines, data models, and core infrastructure. The BI organization will define reporting needs, ensure consistency in metrics and definitions, and drive adoption of data as a decision-making tool across the business.

This role requires strong leadership, stakeholder management, and a passion for building scalable reporting systems and a strong analytics culture.

• Lead and inspire a team of BI / data analysts, fostering a culture of collaboration, ownership, and continuous improvement.
• Mentor and coach team members, supporting professional growth, skill development, and career progression.
• Recruit, develop, and retain top BI talent; set clear performance expectations and provide ongoing feedback.
• Own the company’s reporting strategy and execution, ensuring business-critical metrics and dashboards are accurate, consistent, and trusted.
• Define and maintain core KPI frameworks, metric definitions, reporting standards, and governance (single source of truth).
• Deliver executive-level reporting and key insights that guide strategic decisions, growth, efficiency, and risk management.
• Partner with leaders across Product, Growth, Trading, Fraud, Finance, and Operations to understand needs and translate them into scalable reporting solutions.
• Collaborate closely with the Data Engineering team to define requirements and priorities, ensure data quality and accessibility, improve data models and semantic layers for reporting.
• Drive alignment across teams on reporting definitions, tooling adoption, and analytics best practices.
• Oversee planning and delivery of BI initiatives, ensuring they align with business priorities, timelines, and high quality standards.
• Establish best practices for analytics workflow: QA, metric validation, documentation, dashboards lifecycle management, and stakeholder communication.
• Proactively identify reporting gaps, data inconsistencies, or bottlenecks - and work with partners to resolve root causes.

• Experience in fintech, trading, crypto, or risk/compliance data domains.
• Proven experience leading BI / Analytics / Reporting teams, ideally in high-growth environments.
• Strong stakeholder management and communication skills, including the ability to translate complex data into clear business narratives.
• Experience with team building, performance management, mentorship, and talent development.
• Strong analytical mindset with the ability to identify and solve complex business problems through data.
• Deep understanding of KPI design, reporting frameworks, metric governance, and dashboard best practices.
• Strong proficiency in SQL, Python, Big Query and Google Cloud Environments and a strong understanding of data modeling concepts.
• Strong project management capability: scoping, planning, prioritization, execution, and delivery.
• Proactive approach to addressing challenges and finding innovative solutions.
• Experience with modern BI tooling and semantic layers (e.g., Looker, Tableau, Power
  
  BI, dbt metrics layers, etc.).
• Familiarity with data stack concepts such as Airflow, Big Query, Spark, or streaming pipelines - enough to collaborate effectively with engineering teams.