Data Engineering Manager

Messy spend management is tricky business. 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: You’ll join the Data team to drive innovation and deliver impactful solutions that power our business. We are looking for a Data Engineering Manager to lead our Data Platform team. In this role, you will pick up the torch from our previous manager, moving the focus towards execution, people leadership, and scalability. You will manage a talented team of 5 Data Platform Engineers responsible for the core foundations of Pleo’s data stack (BigQuery, Airflow, Kafka, Terraform). While embedded in the Data Platform Hub, you’ll work directly with the Director of Data to ensure our infrastructure enables the 'Self-Service' vision, enabling Data Products and allowing analysts and engineers to move fast with confidence.

What you’ll be doing:

• Empower the Team (People First): Manage, mentor, and grow your team. You will foster a culture of psychological safety, handle performance reviews, and ensure your engineers have clear growth paths.
• Deliver the Platform Roadmap: You will lead the delivery of critical infrastructure projects. This isn’t just about maintenance; it’s about executing our 2026 strategy, scaling the data platform infrastructure and removing tech debt.
• Operational Excellence: You will ensure our platform is stable, secure, and cost-efficient. You’ll drive best practices in DataOps, CI/CD, and observability to keep our data pipelines robust.
• Enable 'Self-Service': You will continue to support the team’s focus from 'servicing tickets' to building tools that empower the rest of the company (e.g., focus especially on automation).

To put things in context, we’ve listed below examples of previous or upcoming projects we expect from the Data Engineering Manager to work on so you can get a better idea of what you might be doing:

• Performance Reviews: Collect feedback and assess the performance of your team, identify where they might need help or where we can enable them more effectively.
• Align with the Engineering organisation on larger projects around e.g. deprecations or new standards being developed or implemented.
• Data platform rearchitecture: work closely with Staff & Principal level Data Engineers across data to create a long term architecture for the data platform.
• Translate Data platform vision into an actionable roadmap: Work with stakeholders and senior engineers to break down the Data platform vision into a viable roadmap of deliveries.
• Data lake / warehouse migration: Discovery and migration planning for deprecating a legacy data warehouse and replacing it with a modern modular data architecture.

In addition to this, you can expect to work with the following tech stack at Pleo: We’re working with both AWS and GCP as well as Kubernetes as we have a hybrid infrastructure. We of course work with Python and SQL alongside Airflow for orchestration and Kafka for event-driven processing. Our data warehouse currently is in BigQuery, serving dbt and Looker.

What you bring: We are looking for a strategic thinker who is also a 'people-first' leader.

• Engineering Management Experience: You have a proven track record of managing data engineers, handling hiring, and driving team performance.
• Platform Expertise: You have a strong technical background in Data platforms and understand how to architect for scale. You can speak the language of your team.
• Governance & Security Mindset: You have experience implementing data governance tools (Catalogs, PII masking) and understand the importance of security in a Fintech environment.
• Stakeholder Empathy: You are skilled at bridging the gap between technical complexity and business needs, ensuring our Product and Analytics teams feel supported.

Why is this role a good fit for you: This role is a good fit for you if:

• You are a passionate people leader: you find satisfaction in unblocking others and seeing your team succeed rather than writing every line of code yourself.
• You want to create impact: you will own the infrastructure that powers the entire company’s decision-making.
• You are excited about advancements in AI and data engineering best practices.
• You value autonomy: You want to shape how we deliver on our strategy, not just follow a ticket list.

This role is not a good fit for you if:

• You are not comfortable navigating ambiguity and rapid changes.
• You prefer to work in very large, highly distributed, big data environments.
• You are more excited about personally delivering technical work rather than enabling your team to excel.
• You have not previously managed a Data Platform team.

The package: The annual salary for this position varies based on your location: Denmark: DKK 892,497 - 985,855 per annum. The package also includes share options as well as the benefits listed below. 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.

Benefits include:

• 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 holiday + your public holidays
• Hybrid and fully remote working options
• Option to purchase 5 additional days of holiday through a salary sacrifice
• Access to free mental health and well-being support
• Paid parental leave

The Interview Process: Intro call: A 30‑minute chat with our Talent Partner to discuss the role and your background. Hiring Manager interview: a 60‑minute discussion with the hiring manager to dive deeper into your experience and our data vision. A code review interview: a 60‑minute live session where you’ll review real data engineering code alongside our team. A system design interview: a 75‑minutes live session where you’ll work on a data architecture case alongside our team. A leadership interview: a 45‑minutes discussion with a senior leader focusing on behavioural skills and values.

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!

• CV writing and content: we receive a lot of CVs, and many of them are AI‑generated. We love seeing people leverage AI—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 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.
• Application care: every single application we receive is reviewed by a human because we believe that candidates’ efforts should be matched by an equal level of human care.
• Profile to role fit: it is common to see misunderstanding about the level of experience / seniority we expect from a (Data) Engineer Manager. In this role, you are primarily a people manager and need to have solid proven experience on that front.

We’re looking for new friends, gifted minds, team players, restless talents and passionate problem solvers.