Director of Business Intelligence, Cognism

• 10+ years’ experience in BI, analytics, data engineering or data architecture in a SaaS / recurring revenue environment
• Hands-on operator with expert SQL and strong data modelling foundations (player–manager mindset)
• Direct experience designing modern data stacks (warehouse, ETL/ELT, BI tools — technology agnostic)
• Proven ability to build and manage BI or data teams in Series C+ or high-growth SaaS companies
• Strong command of SaaS metrics including ARR, churn, NDR/GDR, pipeline conversion and product usage analytics
• Excellent cross-functional partnership skills across GTM, Product, CS, People and Finance
• Outstanding communication and insight generation, with executive-ready presentation capability
• We welcome applications from individuals typically underrepresented in tech, so if this role excites you but you’re unsure if you meet every requirement, we encourage you to apply!

Desirable

• We’re looking for a highly hands-on, commercially minded Director of Business Intelligence to build and own Cognism’s end-to-end data and analytics environment
• You’ll lead a player–manager BI function responsible for architecting our data lake, warehouse, ETL/ELT pipelines, modelling layers, governance frameworks and visualization systems
• The role partners closely with the C-suite, delivering accurate insights, consistent KPIs and scalable analytics for a global SaaS business
• Design and implement Cognism’s complete data architecture, including warehouse, lake, ETL/ELT pipelines, modelling layers and BI tooling
• Build and lead a BI organisation spanning data engineering, analytics engineering and BI/insights
• Own Cognism’s KPI framework, ensuring consistent definitions across ARR, churn, NDR/GDR, pipeline performance, product usage and people metrics
• Deliver Executive and Board-level dashboards, reporting and insights that drive decision-making
• Partner with GTM, Product, CS, People and Finance to improve forecasting accuracy, churn prediction, GTM efficiency and product adoption
• Establish data governance, including data quality, access controls, lineage and documentation
• Collaborate with Product and Engineering on event tracking, data capture and instrumentation
• Champion self-serve analytics and improve data literacy across Cognism