Nscale
Technology
DataEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Engineer at Nscale. Skills: Data engineering, Palantir Foundry, Data pipelines, Data modelling. Design scalable data pipelines. Build scalable data pipelines”
Industry & Context.
Troubleshooting
What They're Looking For.
Must Have
Deep, hands-on experience building in Palantir Foundry, Proficiency in Python, Experience applying data engineering libraries, Practical experience working in Git-based development workflows, Comfort working in ambiguous, early-stage environments, Clear communication skills
Nice to Have
Experience with cloud platforms, Familiarity with infrastructure telemetry, Familiarity with distributed systems, Familiarity with monitoring data, Familiarity with usage-based billing data, Experience supporting customer-facing data products, Experience supporting customer-facing platforms
What You'll Do.
Design scalable data pipelines
Build scalable data pipelines
Ingest data from infrastructure
Ingest data from platform services
Ingest data from business systems
Implement permissioning
Create trusted datasets
Create trusted metrics
Enable self-serve analytics
Establish data contracts
Establish data documentation
Establish semantic layers
Build capacity planning use cases
Build cost optimisation use cases
Build reliability analysis use cases
Build customer reporting use cases
Collaborate with Product teams
Collaborate with Commercial teams
Translate questions into solutions
Implement data quality checks
Implement data monitoring
Implement data alerting
Codify data freshness
Codify data consistency
Establish data versioning best practices
Establish access control best practices
Establish data governance best practices
Improve system resilience
Improve system observability
Take end-to-end ownership
Define data standards
Define data ways of working
Contribute to technical decision-making
Act as thought partner
How You'll Work.
Team & Collaboration
Operations teams; Infrastructure teams; Platform Engineering teams; Product teams; Commercial teams; Technical stakeholders; Non-technical stakeholders
Communication Scope
Explain data concepts
Full Job Description
. 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 Data Engineer to help design, build, and operate the data foundations that underpin Nscale’s platform, internal operations, and customer-facing capabilities. This is a high-impact, early-stage role. You’ll work closely with Operations, Infrastructure, Platform Engineering, Product, and Commercial teams to turn raw operational signals — from GPUs, clusters, customers, and internal systems — into reliable, scalable data products that ensure delivery at a previously unseen pace. You’ll help define how data is collected, modelled, served, and trusted across the company, and have the opportunity to build on Palantir Foundry, as well as other products. This role is ideal for someone who enjoys building data systems from first principles, thrives in ambiguous environments, and wants to see their work directly influence product decisions, platform reliability, and customer outcomes. What You’ll be Doing (Responsibilities) Data Platform & Architecture ● Design and build scalable, reliable data pipelines that ingest data from infrastructure, platform services, and business systems. ● Define data models a
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