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Data Engineer/MLOps Engineer

Cleo

United Kingdom

Hybrid

GBP 50,000 - 90,000

Full time

6 days ago
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Job summary

Join a forward-thinking company on a mission to revolutionize financial management. As a Data Engineer / MLOps Engineer, you'll play a pivotal role in shaping data-driven solutions that enhance product efficiency and user experience. This role offers the opportunity to work with cutting-edge technologies, mentor talented engineers, and directly influence how data impacts business goals. With competitive compensation, flexible working arrangements, and a commitment to inclusivity, this position is perfect for those looking to make a significant impact while growing professionally in a supportive environment.

Benefits

Competitive Compensation
Flexible Working Arrangements
Generous Annual Leave
Private Medical Insurance
Enhanced Parental Leave
Mental Health Support
Employer-matched Pension

Qualifications

  • Strong knowledge of data system design and problem-solving.
  • Proficiency in Python with software engineering best practices.

Responsibilities

  • Collaborate with product teams to implement scalable data pipelines.
  • Mentor engineers and data scientists in best practices.

Skills

Python
Data System Design
MLOps
Data Pipelines
Cross-functional Communication

Tools

Docker
Kubernetes
Terraform
Spark
Kafka

Job description

About Cleo

At Cleo, we're not just building another fintech app. We're embarking on a mission to fundamentally change humanity's relationship with money. Imagine a world where everyone, regardless of background or income, has access to a hyper-intelligent financial advisor in their pocket. That's the future we're creating.

Cleo is a rare success story: a profitable, fast-growing unicorn with over $200 million in ARR and growing over 2x year-over-year. This isn't just a job; it's a chance to join a team of brilliant, driven individuals who are passionate about making a real difference. We have an exceptionally high bar for talent, seeking individuals who are not only at the top of their field but also embody our culture of collaboration and positive impact.

If you're driven by complex challenges that push your expertise, the chance to shape something truly transformative, and the potential to share in Cleo's success as we scale, while growing alongside a company that's scaling fast, this might be your perfect fit.

Follow us on LinkedIn to keep up to date with new product features and insights from the team.
About the role

We're hiring a Data Engineer / MLOps Engineer to support Cleo's product teams in delivering impactful data-driven solutions. In this role, you'll help teams adopt our internal Data Platform, build efficient data pipelines, and deploy machine learning models effectively at scale. You'll serve as a bridge between product teams and our Data Platform team, ensuring tools and infrastructure meet real-world needs and continuously evolve.

You'll combine hands-on technical work with strategic collaboration, directly influencing how Cleo leverages data to achieve product and business goals.
What you'll do:
  • Collaborate closely with product teams to implement robust, scalable data pipelines and ML workflows.
  • Guide teams in adopting best practices around data engineering, infrastructure management, and MLOps.
  • Surface practical insights from product teams to inform improvements in our internal Data Platform.
  • Contribute actively to enhancing our data and ML infrastructure-focusing on usability, efficiency, reliability, and cost-effectiveness.
  • Mentor and support engineers and data scientists in data engineering and MLOps best practices.
What you'll need:
  • Strong knowledge of data system design; ability to break down problems and propose effective solutions.
  • Proficiency in Python, with a strong understanding of software engineering best practices (testing, automation, code quality).
  • Experience with containerisation and orchestration (Docker and Kubernetes).
  • Infrastructure as Code (Terraform or similar).
  • Experience with at least one distributed data-processing framework (Spark, Flink, Kafka, etc.).
  • Familiarity with different storage solutions (e.g., OLTP, OLAP, NoSQL, object storage) and their trade-offs.
  • Product mindset and ability to link technical decisions to business impact.
  • Excellent cross-functional communication-able to partner with data scientists, software engineers, and product managers.
Nice-to-Haves:
  • Experience with streaming platforms and understanding stream/table transformations.
  • Familiarity with ML system deployment and management (Kubeflow, MLflow, Airflow, Flyte, etc.).
  • Knowledge of monitoring, alerting, and operational best practices for data-intensive systems.
  • Experience with Feature Stores or similar ML data management tools.
What We Offer:
  • Competitive compensation (base + equity), with clear progression frameworks and bi-annual reviews.
  • Flexible working arrangements-hybrid if you're near London, fully remote elsewhere.
  • Generous annual leave (starting at 25 days + public holidays, increasing with tenure).
  • Private medical insurance, enhanced parental leave, mental health support, employer-matched pension, and more.
  • A genuinely supportive, inclusive culture that encourages professional and personal growth.
Explore our progression framework and salary bands

We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds.

If there's anything we can do to accommodate your specific situation, please let us know.

UK App access: The Cleo app is no longer downloadable in the UK (but only until next year). If you're an existing user, you'll still have access to the app. But some features won't be available (just for a little while). Why? 99% of our users are based in the US - where financial health is often overlooked. We've decided to shift our focus to where we can provide the most value and make the greatest impact for users who need it most. Then we'll be able to apply what we learn to better support our UK users in the future.
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