Data Engineering Manager

Confirmed live in the last 24 hours

Pleo

Compensation

£104,000 - £115,000

United Kingdom, London, Spain, Madrid, Denmark, Copenhagen

Hybrid

Posted January 22, 2026

Job Description

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

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.