Senior Data Platform Engineer (m/f/d) in London

Senior Data Platform Engineer (m/f/d) in London

London Full-Time No working from home possible
DeepL

At a Glance

  • Tasks: Build and evolve data platform infrastructure, enabling AI-powered workflows and ensuring data reliability.
  • Company: Join DeepL, a leading AI product company transforming global communication.
  • Benefits: Enjoy flexible hours, hybrid work, competitive salary, virtual shares, and 30 days of annual leave.
  • Other info: Participate in monthly hack sessions and regular team events to foster creativity and collaboration.
  • Why this job: Shape the future of AI while working in a vibrant, diverse team dedicated to innovation.
  • Qualifications: Experience in cloud data infrastructure, Python proficiency, and a reliability mindset.

Meet DeepL. DeepL is a global AI product and research company focused on building secure, intelligent solutions to complex business problems. Over 200,000 business customers and millions of individuals across 228 global markets today trust DeepL's Language AI platform for human-like translation, improved writing and real-time voice translation.

Founded in 2017 by CEO Jaroslaw “Jarek” Kutylowski, DeepL now has around 1,000 passionate employees and is supported by world-renowned investors including Benchmark, IVP, and Index Ventures. Our goal is to become the global leader in trusted, intelligent AI technology, building products that drive better communication, foster connections, and create a meaningful impact. If you’re ready to shape the future of AI and grow your career in a fast-moving, purpose-driven environment, DeepL is your next destination.

What sets us apart is our blend of cutting-edge AI technology, meaningful work, and a culture where people truly thrive. This might be because of our technology that helps millions of people and businesses communicate and work better every day, or because of the trust, curiosity, and care that shape our culture.

DeepL is not just a translation tool; we are building the Operating System for Global Communication. We are the rare AI company that builds the entire stack in-house: from training next-gen LLMs on our own NVIDIA DGX SuperPODs to delivering real-time Language AI to over 300 million users and 200,000+ businesses globally.

We are shifting gears. We are moving from "Software-First" to "Product-First." The decisions behind every model improvement, every product launch, and every business milestone run on data. The Data Platform team is the engineering foundation that makes that possible.

We build and operate the infrastructure that the entire company relies on to work with data effectively — ingestion infrastructure, a reliable lakehouse, the tooling that data engineers build on top of, and increasingly, AI-powered interfaces (MCP connectors, workflow skills, and integrations) that bring data directly into how people and AI agents get work done across DeepL. Our customers aren't just data teams; We're looking for engineers who care as much about the experience of the people who use their systems as they do about the quality of the systems themselves, who take responsibility from architecture to production, and who find meaning in work whose impact compounds quietly across an entire organization.

Your responsibilities

  • Build and evolve the data platform infrastructure: shape and advance the core infrastructure our data ecosystem runs on — our Databricks-based lakehouse, Kafka consumers that reliably ingest data at scale, and the foundational layer that data engineers build their workflows on top of.
  • Enable AI-powered data workflows: build the connectors, interfaces, and integrations that bring data into the hands of humans and AI agents alike, including MCP connectors and workflow skills that let the rest of DeepL access and work with data in AI-assisted workflows.
  • Make data trustworthy at scale: build the systems that make data reliable, not just available. Implement data observability, quality frameworks, monitoring and alerting that give every data consumer confidence in what they work with, and give the team visibility to catch problems before they become incidents.
  • Steward infrastructure, developer experience, and governance: take responsibility for how the platform is built and operated — infrastructure-as-code (Terraform/Terragrunt), CI/CD for data workflows, access management, security configurations, audit trails, and spend governance.

Qualities we look for

  • Must-have:
    • Cloud data infrastructure experience — solid, hands-on experience building and operating cloud-based data infrastructure; comfortable with infrastructure-as-code (Terraform/Terragrunt), CI/CD for data workflows, and container technologies (Docker/Kubernetes).
    • Python proficiency — writes production-quality Python code. Python is our primary language on the Data Platform; familiarity with Go or Java is a plus but not required.
    • Reliability and operational excellence — brings a reliability mindset to data: builds for observability, writes meaningful alerts, owns systems in production, and turns incidents into durable improvements.
    • A platform-product mindset — treats the engineers, analysts, and teams who build on the platform as primary users; thinks deeply about developer experience and reduces friction proactively.
  • Expected:
    • Clear, cross-functional communication — communicates effectively across different audiences, actively seeks feedback from data consumers, and uses that input to improve the platform.
    • AI-native velocity — actively uses AI-powered tools to move faster and take on harder problems, freeing focus for the decisions that matter: architecture, system design, and the tradeoffs that determine whether a platform scales gracefully.
  • Nice-to-have:
    • Lakehouse and streaming technologies — experience with Databricks, Apache Iceberg, Kafka, or similar is a strong advantage.

What we offer

  • Diverse and internationally distributed team: joining our team means becoming part of a large, global community with people of more than 90 nationalities.
  • Open communication, regular feedback: as a language-focused company, we value the importance of clear, honest communication.
  • Hybrid work, flexible hours: we offer a hybrid work schedule, with team members coming into the office twice a week.
  • Virtual Shares - An ownership mindset in every role. We believe everyone should share in our success, and that’s why every employee receives Virtual Shares.
  • Regular in-person team events: we bond over vibrant events that are as unique as our team.
  • Monthly full-day hacking sessions: every month, we have Hack Fridays, where you can spend your time diving into a project you're passionate about.
  • 30 days of annual leave: we value your peace of mind. With 30 days off (excluding public holidays) and access to mental health resources.
  • Competitive benefits: we've crafted it to reflect the diversity of our team and tailored it to align with your unique location.

It’s in our diversity that we will find the power to break down language barriers in the world.

Senior Data Platform Engineer (m/f/d) in London employer: DeepL

DeepL is an exceptional employer that champions innovation and collaboration in the heart of Greater London. With a strong emphasis on employee well-being, we offer generous benefits such as 30 days of annual leave and virtual shares, alongside a vibrant work culture that encourages open communication and team bonding through regular in-person events. Join us to not only advance your career but also to contribute to shaping the future of global communication in a supportive and dynamic environment.

DeepL

Contact Details:

DeepL Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data Platform Engineer (m/f/d) in London

Get Involved in Data Science Meetups

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Show Off Your Projects

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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 DeepL.

Apply Directly through Our Website

When you find a suitable opening like Senior Data Platform Engineer (m/f/d) at DeepL, 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 Platform Engineer (m/f/d) in London

Cloud Data Infrastructure
Infrastructure-as-Code (Terraform/Terragrunt)
CI/CD for Data Workflows
Container Technologies (Docker/Kubernetes)
Python Proficiency
Reliability and Operational Excellence
Data Observability

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 DeepL, 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 DeepL. 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 DeepL

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 DeepL!

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.