Data Platform Engineer in London

Data Platform Engineer in London

London Full-Time 125000 - 140000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and build data pipelines for AI agents to enhance procurement workflows.
  • Company: Join Magentic, a cutting-edge tech company backed by top investors.
  • Benefits: Competitive salary, equity, flexible work, and generous holiday allowance.
  • Other info: Inclusive culture with opportunities for growth and collaboration.
  • Why this job: Shape the future of AI in a $3tn market with a talented team.
  • Qualifications: Experience in data management, DataOps, and building data solutions.

The predicted salary is between 125000 - 140000 £ per year.

We're looking for a Data Platform Engineer to own the data foundation our AI agents run on. Procurement data is messy: ERP transactions, contracts, spreadsheets, PDFs and email, spread across systems that were never designed to talk to each other. You'll build the ingestion pipelines and schemas that turn that into something autonomous agents can reason over, and set the quality and lineage standards that make it trustworthy enough for a Fortune 500 to act on. We’ve built the early foundations but there’s still plenty to build - you’ll shape the architecture to serve hundreds of enterprise customers.

We're building next-generation agentic systems that can manage entire procurement workflows, with a mission to make global manufacturing supply chains more resilient to an ever-changing world. That's a $3tn market opportunity. We're backed by world-class investors including Sequoia Capital, and you'll be joining a team bringing together experience from OpenAI, Meta, Revolut, NASA and McKinsey.

What You’ll Do

  • Design, implement and operate ingestion pipelines processing high-volume data from global supply chain and procurement systems.
  • Define, evolve, and manage data schemas and catalogues—from raw staging to high-quality analytics and feature stores.
  • Build end-to-end monitoring and observability for your pipelines: owning data quality, latency, completeness, and lineage at every stage.
  • Champion secure, governed data practices.
  • Collaborate closely with AI, Platform, and Product teams, provisioning data sets, feature tables, and contracts for analytics and machine learning at scale.

You Might Be a Great Fit if You:

  • Have experience at tech and product-driven companies, with a big focus on data quality, DataOps and data management at scale.
  • Have experience developing data warehouses/lakehouses.
  • Have used a variety of tools across the data stack and can select and implement the right ones for our use case.
  • Are keen to both design and implement data solutions end-to-end.
  • Are comfortable managing your own CI/CD and Integrations.
  • Enjoy communicating with both technical and non-technical stakeholders.

Compensation and Benefits

At Magentic, we recognise and reward the talent that drives our success. We offer:

  • Competitive Equity: play a real part in Magentic’s upside.
  • A salary of £125,000 - £140,000 per annum.
  • Enhanced parental leave.
  • 25 days holiday exc bank holidays, plus an extra day for our Christmas shutdown.
  • In-office lunches provided.
  • Salary sacrifice pension and nursery schemes.
  • Hybrid London HQ (WFH Thurs and every other Tues, with flex if you have appointments etc).
  • Annual team retreat—a fully-funded off-site to recharge, bond, and build.

Our Interview Process

We can move quickly through these stages, so let us know if you have any timelines we need to meet.

  • Initial call (30 mins): this first step is an opportunity for you to hear more about Magentic and the role, and for us to learn more about how your experience aligns with the role.
  • Paired programming interview (45 mins): we'll give you an exercise to demonstrate the key skills for the role.
  • In-person interview: for the final step, we invite you to come meet the team in-person and work alongside us! We find this is the best way for candidates to get a sense of what working at Magentic is like. This will include a culture interview, a founder interview and skills-based interview(s) with the team.

Equal Opportunities and Accommodations Statement

At Magentic, our mission is to build AI that helps solve some of the world's most complex real world problems. We believe building a diverse workforce will be the key to solving this for our customers. Magentic is committed to creating a truly inclusive team and we’re proud to be an equal-opportunity employer. As we grow, we're intentional about building teams with a broad range of backgrounds, experiences and viewpoints, recognising that this leads to better ideas, stronger collaboration and better outcomes for our customers therefore we strongly encourage applications from all backgrounds and cultures to apply. We recognise that some groups remain underrepresented within the industry and are committed to creating an environment that celebrates and supports everyone.

Everyone works differently, and we want to ensure our interview process gives you the best chance to show us what you can do. If you require any reasonable adjustments or accommodations, please let us know and we'll work with you to make the process accessible.

Responsible AI Statement

At Magentic, we are committed to developing artificial intelligence that benefits humanity. We push the limits of AI's capabilities and are dedicated to its responsible and safe deployment. Recognising the profound impact of AI, we ensure that its development is centred around human needs and safety, incorporating a wide array of perspectives to fulfil our mission.

Data Platform Engineer in London employer: Magentic

At Magentic, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to take ownership of their projects and drive innovation in AI-driven enterprise solutions. With competitive compensation, equity opportunities, and a strong emphasis on professional growth, our London HQ offers a collaborative environment where you can thrive alongside a talented team from leading tech backgrounds. Join us in redefining the future of enterprise software while enjoying unique benefits like company-provided meals, a monthly social budget, and an annual team retreat to strengthen bonds and recharge.

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Contact Details:

Magentic Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Platform Engineer in London

Get Involved in Data Science Meetups

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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 Data Platform Engineer at Magentic.

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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 Magentic.

Apply Directly through Our Website

When you find a suitable opening like Data Platform Engineer at Magentic, 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 Data Platform Engineer in London

Data Ingestion Pipelines
Data Quality Management
Data Schema Design
Data Catalogues
Monitoring and Observability
DataOps
Data Warehouse/Lakehouse Development

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 Magentic, 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 Magentic. 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 Magentic

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 Magentic!

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.