Foundry Engineering Lead in London

Foundry Engineering Lead in London

London Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
Nscale

At a Glance

  • Tasks: Lead the design and architecture of Nscale's Foundry implementation for AI-driven data solutions.
  • Company: Join Nscale, a cutting-edge GPU cloud company focused on AI innovation.
  • Benefits: Competitive salary, equity, flexible work environment, and tailored progression plans.
  • Other info: Inclusive culture that values diverse backgrounds and offers human-first flexibility.
  • Why this job: Make a real impact in AI while collaborating with brilliant minds in a dynamic startup.
  • Qualifications: Deep expertise in Palantir Foundry and strong leadership skills in data engineering.

The predicted salary is between 80000 - 100000 £ per year.

About Nscale

Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. Nscale enables AI-focused companies to achieve superior results by reducing the complexity of AI development. Our GPU cloud bolsters technical capabilities and directly supports strategic business outcomes, including cost management, rapid innovation, and environmental responsibility. We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you'll build trust through openness and transparency, where everyone is inspired to do their best work. If you join our team, you'll be contributing to building the technology that powers the future.

About the Role (Job Purpose)

We're looking for a Foundry Engineering Lead to serve as the technical authority for our Foundry implementation at Nscale—leading the design, development, and governance of the data platform that underpins our internal operations, workflows, and customer-facing capabilities. This is a senior, high-impact role at the intersection of hands-on engineering and technical leadership. You'll set the architectural direction for Foundry, build and maintain the core data infrastructure, and work closely with Operations, Infrastructure, Platform Engineering, Product, and Commercial teams to deliver reliable, scalable data products. As the most experienced Foundry engineer in the team, you'll mentor and guide other engineers and analysts, establish standards and best practices, and drive the technical roadmap as the platform scales. This role is ideal for someone who combines deep, hands-on Foundry expertise with the confidence to lead technically—someone who can architect at scale, get into the details when it matters, and bring others along with them.

What You'll be Doing (Responsibilities)

  • Lead the design and architecture of Nscale's Foundry implementation, ensuring scalability, security, and long-term data integrity.
  • Define the technical strategy for Foundry development, aligning with business objectives and the programme-wide data roadmap.
  • Act as the technical authority on Foundry across the organisation—setting standards, driving architectural decisions, and owning the evolution of the platform.
  • Conduct code reviews and ensure adherence to best practices in data modelling, pipeline development, and integration.
  • Mentor engineers and analysts working within the Foundry environment, raising technical capability and quality across the team.
  • Design and build scalable, reliable data pipelines that ingest data from infrastructure, platform services, and business systems.
  • Define data models, schemas, and ontology structures that support operational workflows and use cases across the business.
  • Clean, transform, and structure data to create a digital twin of Nscale.
  • Implement permissioning and manage access and security of the Foundry implementation.
  • Create trusted datasets and metrics that power workflows, internal tools, and customer-facing insights.
  • Enable self-service analytics by establishing clear data contracts, documentation, and semantic layers.
  • Build use cases including, but not limited to:
    • Capacity planning
    • Cost optimisation
    • Reliability analysis
    • Customer reporting
  • Collaborate with Product and Commercial teams to translate real-world business questions into robust data solutions.
  • Implement data quality checks, monitoring, and alerting to ensure data correctness and availability.
  • Codify data lineage, freshness, and consistency across systems.
  • Establish and enforce governance standards around data versioning, access control, and compliance appropriate for a fast-scaling company.
  • Oversee the integration of Foundry with existing systems and data sources, ensuring seamless data flows.

Profile and Required Skills

  • Deep, hands-on expertise in Palantir Foundry, including ontology modelling, pipeline development, data architecture, and large-scale platform design.
  • Proven experience providing technical leadership—setting architectural direction, mentoring engineers, and defining standards in a data engineering context.
  • Strong proficiency in Python, with experience applying data engineering frameworks (e.g. Spark, PySpark, Dask, pandas) to large, complex datasets.
  • Familiarity with API-driven data integration, including REST, GraphQL, and Foundry Action APIs.
  • Experience with Git-based development workflows, including code reviews, version control, and CI/CD pipelines.
  • Excellent communication skills—able to explain complex technical concepts clearly to both technical and non-technical stakeholders.
  • Comfortable operating in ambiguous, fast-moving environments where requirements evolve quickly.
  • A bias toward ownership, pragmatism, and delivering useful solutions.

Nice to Have

  • Experience with cloud platforms (AWS, GCP, Azure) and infrastructure telemetry.
  • Familiarity with distributed systems, monitoring data, or usage-based billing data.
  • Experience supporting customer-facing data products or platforms.

What We Can Offer You

At Nscale, you'll find a collaborative, supportive, and innovative environment where your contributions spark real impact. We're building something extraordinary, and we want you at the core.

  • Highly competitive package (base + equity) with reviews every 12 months.
  • Join the fastest-growing tech startup, your chance to push boundaries, collaborate with brilliant minds, and make your mark on cutting-edge AI.
  • Expect a dynamic progression plan tailored to your ambitions. Grow by trying new things, leading, challenging the status quo, and owning your impact, always with our full support.
  • Human-First Flexibility: We treat you as humans first. Our flexible workplace trusts Nscalers to deliver, giving you the autonomy to shape your day around life's moments.

Equal Opportunities Statement

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. The responsibilities outlined in this job description are not exhaustive and are intended to provide a general overview of the position. The employee may be required to perform additional duties, tasks, and responsibilities as assigned by management, consistent with the skills and qualifications required for the role.

Foundry Engineering Lead in London employer: Nscale

At Nscale, we pride ourselves on fostering a culture of relentless innovation and accountability, making us an exceptional employer for those looking to make a meaningful impact in the AI sector. Our collaborative and supportive environment encourages personal growth and offers a highly competitive compensation package, along with human-first flexibility that allows you to balance work and life seamlessly. Join us in shaping the future of technology while working alongside brilliant minds in a fast-paced, dynamic setting that values your contributions and ambitions.

Nscale

Contact Details:

Nscale Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Foundry Engineering Lead 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 Nscale!

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 Foundry Engineering Lead at Nscale.

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 Nscale.

Apply Directly through Our Website

When you find a suitable opening like Foundry Engineering Lead at Nscale, 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 Foundry Engineering Lead in London

Palantir Foundry
Ontology Modelling
Pipeline Development
Data Architecture
Large-Scale Platform Design
Technical Leadership
Python

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 Nscale, 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 Nscale. 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 Nscale

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 Nscale!

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.