Job Opportunities in the Seedcamp Portfolio

Intro

At Pleo, we’re on a mission to revolutionise the way businesses manage company spending. No more outdated processes, clunky spreadsheets, or frustrating delays - we believe spend management should be seamless, empowering, and surprisingly effective for finance teams and employees alike. We’re creating tools that promote autonomy, foster trust, and let businesses focus on what truly matters.

Our culture is built on transparency, collaboration, and a deep commitment to innovation – which is reflected in our spending solution. At Pleo, you’ll join a passionate team shaping the future of work, all while having some fun along the way.

About the role

We’re looking for an Analytics Engineer to join our Data Service team at Pleo. In this role, you’ll focus on building and refining the data models, semantic layers, and data structures that enable self-serve analytics across the company.

You’ll work closely with analysts and engineers to turn raw data into reliable, documented, and business-friendly datasets. This role is ideal for someone who loves translating complex requirements into clean and scalable models, and who wants to work in a fast-paced, product-led environment where data is core to decision-making.

Please note this role will be open for applications from 25th November 2025 to 1st December 2025 09.00 GMT. We will not review any applications before the closing date so there is no rush to apply, ensure you take the time to submit a high quality application.

What you’ll be doing

As a member of our Data Services team and Analytics Engineering community, you can expect to:

• Design and build data models that power key dashboards, KPIs, and exploratory analyses for business analytics purposes (with a focus on commercial areas).
• Translate business logic into structured, testable, and well-documented datasets used across teams.
• Collaborate with analysts, engineers, product managers, or other business stakeholders to align on definitions, requirements, and model ownership.
• Help standardise modelling conventions and improve scalability and maintainability of our warehouse.
• Implement and maintain testing strategies to ensure data accuracy and trust
• Contribute to our semantic layer (LookML) to enable consistent and scalable reporting.
• Participate in code reviews and continuously improve development workflows within the team.

In case you are curious, here is a list of some of the technologies the team is working with: dbt, BigQuery, Looker (and LookML), SQL, Github Actions (CI/CD), Fivetran, Airflow.

What you bring

You have proven experience collaborating with Analytics Engineers, Data Analysts and commercial stakeholders on analytics initiatives. You also have:

• Solid experience working with dbt and modern cloud data warehouses like BigQuery.
• Strong SQL skills and experience building well-structured, reusable models in a layered architecture.
• Solid understanding of data modelling methodologies such as kimball.
• The ability to translate messy or ambiguous business logic into clean, performant data transformations.
• Familiarity with Git-based workflows, version control, and basic CI/CD practices for analytics code
• A pragmatic and collaborative approach to problem-solving - you know when to ship and when to refactor.
• Experience working closely with stakeholders to clarify requirements and ensure data models meet real-world needs.

Why is this role a good fit for you

This role is for you if:

• You enjoy working with stakeholders, understanding their business needs, and translating them into reusable data models.
• You like collaborating with Analysts and helping them level up in dimensional modelling and the new Analytics Warehouse.
• You’re comfortable switching between different commercial domains (GTM, Finance, People) rather than focusing on a single area.
• You want to work alongside other analytics engineers and contribute to shaping our modeling standards and tooling.
• You enjoy building in a space that’s still evolving, where your feedback and suggestions can influence how we work.

This role may not be for you if:

• You want a purely technical, infrastructure-heavy role.
• You prefer staying in one domain rather than adapting to different business areas.
• You don’t enjoy stakeholder collaboration or translating business context into models.
• You want fully defined processes - our foundations are still being built.

Who you’ll be working with and reporting to

You’ll report to our Data Service Team Lead and work closely with other (Analytics) engineers, and Data Analysts. The Data Service team sits within the central Data Platform Hub at Pleo and plays a key role in enabling scalable, trustworthy analytics across the company.

How you’ll develop in this role

In your first few months at Pleo, you will:

• Get onboarded to our Analytics Warehouse, modeing standards, and dbt workflows.
• Learn how our commercial domains (GTM, Finance, People) use data and where their needs differ.
• Work closely with Analysts to turn business questions into clear modeling requirements.
• Start owning small–medium modeling tasks end-to-end, including tests and documentation.
• Collaborate with other analytics engineers on design reviews, modeling patterns, and semantic layer improvements.
• Contribute ideas and feedback as we refine our processes, standards, and ways of working.
• Help support analysts in understanding dimensional modeling and navigating the new AW environment.

We’re committed to helping you develop your career, whether that means taking on bigger projects, stepping into leadership, or acquiring new skills in software engineering.

The package

The annual salary for this position varies based on your location:

• United Kingdom: £72,000 - £80,000
• Spain & Portugal: €75,000 - €82,500

The role can be based in Portugal, Spain or the UK. We can hire either remotely, hybrid or in office but you need to be physically based in any of those countries.

Please note we are unable to offer visa sponsorship for this role in any of the listed locations you find in the job info so you will need to have a valid right to work.

We’re happy to share more about our approach to pay and this range during your first call with us!

Show me the benefits!

• 💳 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
• 🌴 We offer 25 days of holiday + your public holidays
• 🏠 For our Team, we offer both hybrid and fully remote working options
• 🏖️ Option to purchase 5 additional days of holiday through a salary sacrifice
• ❤️‍🩹 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

The Interview Process

1. Intro call: A 30-minutes chat with our Talent Partner to discuss the role and your background.
2. A Hiring Manager interview: A 60-minutes meeting with the team manager to deep dive into your technical experience, domain knowledge and project experience.
3. A technical task: this is a take-home exercise you complete in your own time
4. A Team interview: a 60-minutes interview with the team where we’ll follow-up on your take home challenge and also ask a few technical questions

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!

Last time we hired an Analytics Engineer, we received a total of 173 applications but only 10 were selected for an intro call. Some of the key reasons why previous candidates didn’t make it past the application screening stage include:

• CV writing and content: it was very clear that many of the CVs we saw were very generic and AI generated. There is no issue with leveraging AI to help with CV writing, there was little indication of what real impact the candidates had in their previous experience. You might have heard of the “Achieved X, as measured by Y, by doing Z” formula (credit Laszlo Bock ~2014), this is a great way to give a clear picture of what you have actually worked on. Some link or quick description of the companies you’ve worked with is also a great help.
• Application care: 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.
• Profile to role fit: there was misunderstanding about the type of experience we expect from an Analytics Engineer and we received many applications from candidates who had never been exposed to a product-led environment or had been exclusively focused on SQL/dbt work when we’re looking for both technical and stakeholders management and team collaboration experience. We’ve taken great care in writing this role description to reflect the reality of the job as best as possible, please ensure you read it carefully and highlight on your CV the experience relevant to what we are looking for.

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