Staff Fullstack Data Analyst (Commercial Analytics)

About the role

About Pleo Messy spend management is tricky business. And tedious processes are a lose-lose situation for all involved, not just finance. At Pleo, we're changing that. We build spend solutions that make managing money seamless, empowering, and surprisingly effective for finance teams and employees alike - with a vision to help all businesses ‘go beyond’. The word ‘Pleo’ actually means ‘more than you’d expect’, and living by that mantra has been the secret to our success over the last 10 years. Now, we’re at a pivotal moment in our journey; every move we make has a direct impact on our 40,000+ customers, our business, and our collective success. We need people who take pride in uncovering customer needs, who turn complex problems into simple solutions, challenge the way things are done (respectfully), and always aim high. With great ambitions driving us forward, we can’t say we’ve got this whole thing figured out. And frankly, that’s half the fun! What we can say is that we’re a driven, progressive, and, importantly, a kind bunch of 850+ people from over 100 nationalities, all committed to delivering the future of business spending, together. Please note: Applications will be open until 3rd October 2026 at 10.00 CEST. We will not review any application before the closing window so, please, don't rush to apply and ensure you use the time to submit a high quality, personalised application. About the role Growth Intelligence owns the commercial data layer that powers Pleo's GTM engine — acquisition, retention, propensity modelling, and customer health. The team supports RevOps, Customer Experience, Customer Success, and senior commercial leadership with the data and models they need to make faster, smarter decisions. As a Staff Full Stack Data Analyst, you are the senior technical voice for commercial analytics at Pleo. You set the architectural direction for Growth Intelligence's analytics layer, define what good looks like for the team, and shape how GTM data is structured, governed, and consumed by people and increasingly by AI tools. You bring technical depth, commercial instinct, and organisational reach in equal measure. You move between architecture reviews and executive presentations, between defining metric contracts and mentoring the analysts who implement them. You don't just answer questions - you identify the right ones, and you make sure the answers compound over time. Who you'll work with You will report to the Senior Manager of the Growth Intelligence team. You will partner closely with senior commercial leadership, Customer Experience, Sales, and Customer Success teams; the onboarding and self-serve product teams; Data Scientists and Analytics Engineers across the broader data organization; and Data Services & Governance on standards and semantic layer ownership. You will be a visible, senior presence across the entire data community at Pleo. What you'll be doing Own the architectural direction of the analytics layer for customer acquisition, onboarding, growth, and retention. You'll be making systemic decisions about how models are structured, layered, and governed, not just what gets built next. Identify and resolve upstream data quality issues at source, treating quality gaps as governance and contract problems, articulating the business risk they create, and driving the org-level changes needed to fix them durably. Define canonical GTM metric definitions in the semantic layer, in partnership with Data Services & Governance while ensuring RevOps, CS, CX, BI tools, and AI tooling are working from the same source of truth, and holding that standard over time. Partner with senior commercial leadership to shape the questions worth answering. Lead in-depth analysis of customer behaviour, commercial performance, and retention patterns. Design and govern the team's approach to experimentation ensuring statistical rigour, scalable methodology, and clear criteria for what constitutes a meaningful result. Build analytics explicitly architected for self-serve and AI access: structured, documented, and reliable enough for business teams, conversational analytics tools, and AI features to consume autonomously. Mentor and develop analysts on the team through code reviews, design discussions, and deliberate knowledge-sharing, raising the collective standard of analytical craft. Contribute to engineering and analytical standards across the broader data community, participating in cross-team reviews and helping define what production-grade analytics looks like at Pleo. For extra context, you'll also be leveraging technologies including SQL, dbt, BigQuery, Looker, Amplitude, HubSpot, Zuora, or Vitally. What you bring Prior experience operating at Staff or Lead level in data analytics or analytics engineering roles in a fast-paced SaaS organisation. Expert knowledge of SQL and dbt: you write clean, tested, well-architected models and can make and defend layering decisions for a team, not just yourself. Solid proficiency with Python for data analysis and manipulation. Comfort with Git-based workflows and CI/CD practices for analytics code. BigQuery fluency, including performance optimization and cost considerations at scale. Mastery of a modern BI tool such as Looker or Omni. Commercial specialisation: you have worked in a commercial analytics focused role and understand GTM metrics, customer lifecycle economics, and how data connects to revenue outcomes at a strategic level. Systems thinking on data quality: you approach quality gaps as governance questions, identify root causes upstream, and drive fixes that last rather than patches that don't. Strong understanding of data contracts: schema ownership, SLAs, and the organizational dynamics required to make producer-consumer agreements stick. Understanding of how analytics outputs serve AI tools and self-serve analytics as first-class consumers: you design for machine access as well as human access, and you know why metric consistency become