At a Glance
- Tasks: Build and evolve AI data workflows and infrastructure for a leading tech company.
- Company: Join DeepL, a global leader in AI solutions with a focus on innovation.
- Benefits: Enjoy hybrid work, competitive pay, 30 days leave, and mental health resources.
- Other info: Participate in monthly hacking sessions and regular team events for collaboration.
- Why this job: Make an impact by designing cutting-edge data workflows that empower users and AI.
- Qualifications: Experience in cloud-based data infrastructure and proficiency in Python required.
The predicted salary is between 63000 - 77000 £ per year.
DeepL is a global AI product and research company focused on secure, intelligent solutions for complex business problems. Its Language AI platform provides human-like translation, improved writing, and real-time voice translation for individuals and businesses worldwide.
Responsibilities:
- Build and evolve data platform infrastructure, including the Databricks-based lakehouse, Kafka consumers, and foundational tooling for data engineers.
- Support and extend dlt to make data ingestion patterns reusable and robust.
- Make technical decisions that enable the platform to scale with DeepL’s data volume and use-case diversity.
- Build connectors, interfaces, and integrations that bring data to humans and AI agents, including MCP connectors and workflow skills.
- Design AI-powered data workflows for data engineers, analysts, business teams, and AI tools.
- Implement data observability, quality frameworks, monitoring, and alerting.
- Own infrastructure-as-code, CI/CD for data workflows, access management, security configurations, audit trails, and spend governance.
- Build golden-path templates and patterns that help engineers across the company use data safely and efficiently.
Requirements:
- Hands-on experience building and operating cloud-based data infrastructure.
- Experience with Terraform/Terragrunt, CI/CD for data workflows, and Docker/Kubernetes.
- Production-quality Python proficiency.
- Reliability mindset, including observability, meaningful alerts, production ownership, and incident-driven improvements.
- Platform-product mindset focused on developer experience and reducing friction for platform users.
- Communicates effectively across different audiences and actively uses feedback from data consumers.
- Actively uses AI-powered tools to move faster and focus on architecture, system design, and scalability tradeoffs.
Nice to have:
- Experience with Databricks, Apache Iceberg, Kafka, or similar lakehouse and streaming technologies.
Conditions:
- Hybrid work schedule with office attendance twice a week and flexible working hours.
- Virtual Shares for every employee.
- Regular in-person team events.
- Monthly full-day hacking sessions.
- 30 Days of annual leave excluding public holidays.
- Mental health resources.
- Competitive benefits tailored to the employee’s location.
platform engineer for AI data workflows in London employer: Enfint
DeepL is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the field of AI. With a hybrid work schedule, competitive benefits, and ample opportunities for professional growth, employees are empowered to thrive while contributing to cutting-edge projects. The company's commitment to mental health resources and regular team events further enhances the supportive environment, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land platform engineer for AI data workflows in London
✨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 Enfint!
✨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 platform engineer for AI data workflows at Enfint.
✨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 Enfint.
✨Apply Directly through Our Website
When you find a suitable opening like platform engineer for AI data workflows at Enfint, 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 platform engineer for AI data workflows in London
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 Enfint, 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 Enfint. 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 Enfint
✨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 Enfint!
✨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.
