Senior Data Engineer (Commercial Analytics)

Senior Data Engineer (Commercial Analytics)

Full-Time 59400 - 72600 £ / year (est.) Home office (partial)
P

At a Glance

  • Tasks: Design and maintain data pipelines to connect commercial tools and our BigQuery data warehouse.
  • Company: Join Pleo, a progressive tech company transforming spend management for businesses.
  • Benefits: Enjoy a Pleo card, catered lunches, private healthcare, and 25 days of holiday.
  • Other info: Flexible remote or hybrid working options available, with excellent career growth opportunities.
  • Why this job: Be part of a dynamic team that values innovation and collaboration in data engineering.
  • Qualifications: Experience in building production data pipelines and strong knowledge of CRM data models.

The predicted salary is between 59400 - 72600 £ per year.

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.

About the role

We're looking for a Senior Data Engineer to join our Growth Intelligence team at Pleo. In this role, you'll design and maintain the integration architecture and data contracts that connect our commercial and GTM data layer (the pipelines linking our CRM, billing, and customer success tooling to a central BigQuery warehouse) and be part of the team as we scale our commercial data foundations to support RevOps, Customer Success, and the AI products built on top of them. If you're excited about untangling complex, multi-system architecture and are passionate about building data foundations the whole business can trust, then this is the opportunity for you!

Who you’ll be working with and reporting to

You’ll report to the Senior Manager of Growth Intelligence and work closely with the RevOps and the BAT (Business Architecture & Technology) teams to understand what commercial operations needs from data. Our team is highly collaborative and dedicated to keeping Pleo's commercial and GTM data trustworthy and well-governed. You’ll also partner with Analytics Engineers to ensure pipeline outputs are modelling-ready, and engage upstream with tool owners and engineering teams to push data quality and schema discipline closer to the source.

What you’ll be doing

  • Design, build, and maintain data pipelines between commercial tools (HubSpot, Zuora, Vitally) and our BigQuery data warehouse.
  • Own reverse ETL flows: enrich or define data in the warehouse and push it back into operational tools like HubSpot, keeping definitions consistent across systems.
  • Implement and maintain data contracts with clear ownership, SLAs, and schema agreements between data producers (tool owners, product engineers) and data consumers (analysts, RevOps, AI tooling).
  • Partner with RevOps and the BAT team to understand operational data requirements and translate them into reliable, governed pipelines.
  • Build monitoring and alerting that catches data quality issues before they surface in dashboards, operational reports, or downstream models.
  • Simplify integration architecture by centralising data flows through the warehouse, reducing point-to-point tool integrations and the maintenance burden that comes with them.
  • Work with Analytics Engineers to ensure pipeline outputs are structured and documented for downstream modelling.
  • Engage upstream with tool owners and engineering teams to move data quality and schema discipline closer to the source.

Our commercial data stack connects subscription billing (Zuora), CRM (HubSpot), and customer success tooling (Vitally) to a central BigQuery data warehouse. You can expect to work with the following tech stack: BigQuery, Python, HubSpot, Zuora, and Vitally plus dbt, Fivetran/Census, or Airflow depending on your background.

What you bring

  • Proven experience building and maintaining production data pipelines in a commercial or GTM data environment.
  • Strong understanding of CRM data models, APIs, and field management (HubSpot or comparable experience).
  • Hands-on experience with reverse ETL patterns: pushing warehouse-enriched or warehouse-defined data back into operational tools.
  • Extensive BigQuery experience.
  • Experience implementing data contracts in a production environment.
  • Python proficiency for pipeline development, transformation logic, and tooling.
  • Git-based workflows and CI/CD experience for data engineering code.

Why is this role a good fit for you

This role is a good fit for you if:

  • You are equally excited by deep technical work as you are by collaborating with business stakeholders.
  • You can comfortably work with a wide variety of data sources and can operate within a complex multi-system environment.
  • You truly shine at solving problems and driving alignment between GTM/commercial stakeholders.

This role is not a good fit for you if:

  • You prefer to work on platform matters that are one step removed from the business.
  • You have never collaborated with senior stakeholders on GTM / commercial analytics work.
  • You need a very defined roadmap and backlog to operate efficiently. You'll need to adapt to rapid changes and be part of the roadmap definition discussions in this role.

How you’ll develop in this role

In your first 6 months at Pleo, you’ll:

  • Become familiar with our data ecosystem and codebase.
  • Support to drive a HubSpot reimplementation project from the data side.
  • Collaborate with Data Platform & Analytics Engineers as well as GTM teams to improve or commercial analytics efforts.

Please note: We can hire on a remote, hybrid or in-person set-up in any of the locations listed on the advert but you will need to be physically based in the country of your choice with a valid right to work. We are unable to offer visa sponsorship for this role in any of the listed locations.

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
  • 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

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:

  • Intro call: A 30-minute chat with our Talent Partner to discuss the role and your background.
  • Core skills tests: An async coding exercise through our CoderPad third party platform.
  • Hiring Manager interview: A 60-minute chat with your Manager to deep dive into your technical experience and impact.
  • Pleo Challenge: A 75-minute live interview with two colleagues to assess your architecture and problem solving 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!

Last time we hired a Senior Data Engineer, we received a total of 543 applications but only 15 were selected for an intro call. With this in mind, we want to help you understand what we really care about when reviewing your application: 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.

This role requires experience operating within a SaaS organisation, collaborating closely with GTM teams. It is equally important to demonstrate your technical expertise with production pipelines as it is to demonstrate your understanding and impact across commercial analytics.

About your application

  • 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.
  • Interview at your best. We want you to feel comfortable throughout the process. If you have any accessibility requirements or need a specific format, email belonging@pleo.io. We’ll design a process that works for you.
  • Your data is safe. When you apply, we process your personal data as a data processor. For more information on how Pleo processes personal data, read our Privacy Policy here.
  • Applying for multiple roles? Nothing is stopping you, and we assess every role independently. However, we do look for alignment, so make sure you can explain why your interest and experience are right for each specific role.
  • Reapplying. If you’re applying for the same role again, please wait six months from your last decision before hitting submit.

Senior Data Engineer (Commercial Analytics) employer: Pleo

Pleo is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for a Staff Engineer to thrive. With a strong emphasis on employee growth, you will have the opportunity to shape foundational data practices while working with cutting-edge technologies in a supportive environment. Located in a vibrant city, Pleo offers unique advantages such as a diverse team and a commitment to leveraging AI in meaningful ways, ensuring your contributions have a significant impact across the organisation.

P

Contact Details:

Pleo Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data Engineer (Commercial Analytics)

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Pleo!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Engineer (Commercial Analytics) at Pleo.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Pleo.

Apply Directly through Our Website

When you find a suitable opening like Senior Data Engineer (Commercial Analytics) at Pleo, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Data Engineer (Commercial Analytics)

Data Pipeline Development
BigQuery
Python
CRM Data Models
API Integration
Reverse ETL
Data Contracts Implementation

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Pleo, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Pleo. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Pleo

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Pleo!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.