Foundry Engineering Lead

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.