Sales Operations Analyst
About the role and team
Our Sales Operations team powers the strategic and technical engine behind our real-world sales ecosystem.
As a Sales Operations Analyst, you will serve as a high-leverage partner, architecting the data infrastructure, AI workflows, and analytical frameworks needed to drive high-velocity commercial decision-making.
You will bridge complex business requirements and technical roadmaps, transforming multi-billion-dollar operational complexity into seamless systems.
This role is built for a hands-on operator who thrives in ambiguity, navigates cross-functional tension with poise, and scales workflows at massive volume.
What you’ll do
- Architect Data Infrastructure: Design and build scalable data models and pipelines that serve as the foundation for downstream analytics across cross-functional teams.
- Optimise & Automate Workflows: Identify operational bottlenecks and eliminate repetitive manual processes to optimise bandwidth across teams.
- Develop AI-Powered Tools: Build innovative internal AI applications that act as technical infrastructure for sales operations.
- Drive Business Insights: Analyse trends, surfacing actionable insights through dashboards and automated reporting suites.
- Lead Cross-Functional Programs: Partner directly with Commercial and Analytics teams to launch high-stakes strategic initiatives and ensure seamless operational execution.
Basic qualifications
- Experience: 3+ years of experience in sales analytics, data analysis, or operations, with hands-on experience designing and deploying AI-driven workflows.
- Technical Architecture: Solid foundational knowledge of end-to-end AI product architecture, including front-end user interfaces and back-end integration.
- Data Mastery: Advanced SQL proficiency to query and synthesize complex, large-scale datasets, paired with expert quantitative modeling in Excel.
- Proven Environment: Track record of success in a high-growth tech, startup, or management consulting environment.
- Project & Process Management: Demonstrated ability to drive strategic projects while effectively managing competing priorities and tight operational timelines.
- Education: Bachelor’s degree in relevant discipline
Preferred qualifications
- Programming: Proficiency in Python or R for data analysis, automation, and custom modeling.
- Data Science Foundations: Good grasp of core data structures and functional application of data science algorithms.
- Agility & Execution: Thrives in high-velocity environments; able to pivot quickly, act with urgency, and maintain high standards under tight deadlines.