Staff Fullstack Data Analyst (Commercial Analytics)

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.

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.

• 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., * You will have driven at least one meaningful governance outcome: canonical GTM metric definitions agreed with Data Services & Governance, embedded in the semantic layer, and actively used so that analysts, BI tools, and AI features are working from the same numbers.

• You will have established yourself as a trusted partner to commercial leadership, not just the person who delivers the analysis, but the person they bring in when they’re not sure what question to ask.

• You will have shipped something that changed what was possible: not improved plumbing, but unlocked a capability or decision that couldn’t have happened without you.

• Your own Pleo card (no more out-of-pocket spending!)
• Lunch is on us for your work days - enjoy catered meals or receive a lunch allowance based on your local office
• Comprehensive private healthcare - depending on your location, coverage options include Vitality, Alan or Médis
• 25 days of annual leave + public holidays (additional days may apply in select countries based on local standards).
• For our Team, we offer both hybrid and fully remote working options
• We use MyndUp to give our employees access to free mental health and well-being support with great success so far
• Paid parental leave - we want to make sure that we’re supportive of families and help you feel that you don’t have to compromise your family due to work

We want to ensure you are set-up for success and understand what will be expected of you. If your application is successful, our interview process is as follows:

1. Intro call: A 30-minute chat with our Talent Partner to discuss the role and your background.
2. Core skills test: an async technical exercise designed to assess your coding fundamentals.
3. Hiring Manager interview: a 60-minute experience-based interview to deep dive into your domain knowledge, technical expertise and ability to lead initiatives.
4. Pleo Challenge: a live practical and technical case study designed to assess your domain knowledge, problem solving, and insights generation skills.
5. Final interview: a 30-minute conversation with a senior leader focusing on your behavioural skills.

Transparency is important to us so we also wanted to share some insights about what we’re looking for in applications to ensure you can set yourself up for success!

• 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 becomes critical as AI tooling scales.
• Track record of advising senior GTM stakeholders around shaping the question as much as answering it, and communicating risk and tradeoffs clearly to non-technical leaders.
• Experience mentoring analysts and raising team capability

This role is a good fit for you if:

• You excel at turning large, interconnected and complex problems into well structured, clearly defined and pragmatic solutions. If you are comfortable navigating ambiguity within a fast-paced SaaS organisation, and can generate clarity, you’ll find this role very exciting.
• You find hands-on technical work as exciting as stakeholders management, delivery management and governance strategy.
• You have operated as a Technical Lead for Commercial / Growth Analytics within a 500+ people SaaS organisation and understand the recurring topics, challenges and goals businesses of our scale experience.

This role is NOT a good fit for you if:

• You prefer to specialise deeply in one technical area rather than wear multiple hats. This role requires you to move between architecture, analysis, experimentation, stakeholder management, and mentoring.
• You are not comfortable operating at senior leadership level and shaping ambiguous commercial questions into solvable data problems. You’ll often need to define what success looks like before you can measure it.
• You need clean problem definitions before you can start. The commercial data environment here is genuinely complex: definitions evolve, ownership is shared, and the right answer sometimes requires organisational negotiation as much as analysis.
• You think of standards and governance as someone else’s job. At this level, you are part of how the organisation decides what good looks like.

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., * We receive a lot of CVs, and many of them are AI-generated. We love seeing people leverage AI - it’s a big focus for us internally too- but without human intervention, these CVs can sometimes become generic and fail to show a candidate in the best light. What we’re really looking for is the specific details of real impact that only you - not AI - know from your previous experience. A top tip from us is to use the “Achieved X, as measured by Y, by doing Z” formula (credit: Laszlo Bock, ~2014) to give a really clear picture of what you’ve worked on. A final note: including links to your previous companies’ websites is a huge help and allows us to truly understand your background.

• Every single application we receive is reviewed by a human (yes, hundreds of them) because we believe that candidates’ efforts should be matched by an equal level of human care. This means that we expect a similar level of attention put into your application. Read and answer the application questions carefully, they make a huge difference in our decision-making process.

• For this role, technical experience, seniority and commercial domain expertise all matter equally. Ensure your CV reflects the actual experience you have in each of these areas.

• English first. Since it’s our company language, please submit your application in English. You’ll be using it a lot if you join us.
• A fair look for everyone. Our talent team reads every single application to ensure the process is fair. To keep things running smoothly, we only accept applications through our system-our support team can’t pass on calls or emails.
• Diversity drives us. We can only reach our goals if our team reflects the world around us. That starts with you hitting apply, even if you don’t tick every single box. We encourage people from all backgrounds and experiences to join us.