Senior Data and Platform Engineer

🔥 0 minutes ago

🏄 California, New York, +2 more states – Remote

🏄 California – Remote 🗽 New York – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $200k - $322k / year

⏰ Full Time

🟠 Senior

🏗️ Platform Engineer

🦅 H1B Visa Sponsor

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👻 Ghost score 1%

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Define and guide the technical vision for a key DGX Cloud Data Platform domain • Own architecture, interfaces, and growth while planning for scale, reliability, performance, security, compatibility, and cost • Lead technical delivery of complex, cross-team initiatives • Transform unclear requirements into architectures and interfaces, coordinate implementation, write essential code, overcome technical obstacles, and guide secure production integrations • Architect, implement, and evolve batch and streaming systems for fleet, capacity, utilization, cost, scheduling, and operational telemetry • Build shared platform capabilities, including libraries, workflow and orchestration abstractions, deployment tooling, and implementation standards • Lead high-impact production investigations across pipelines, applications, query engines, distributed processing, storage, networks, and cloud services • Establish engineering standards for automated testing, data quality, reconciliation, lineage, service-level objectives, observability, secure identities, least-privilege access, release readiness, and auditable deployments • Establish data models, semantics, ownership boundaries, and serving interfaces across teams • Provide tables, APIs, automation, dashboards, and internal applications for trusted DGX Cloud data access • Provide technical leadership through architecture and build reviews, hands-on mentorship, and resolution of difficult tradeoffs • Raise engineering quality through reusable patterns, clear decisions, and sustained follow-through

🎯 Requirements

• 12+ years of relevant industry experience • Bachelor’s degree or equivalent experience • Master’s degree or equivalent experience in Computer Science, Engineering, or a related field • Sustained hands-on experience crafting, implementing, and operating production software, data platforms, databases, or distributed systems • End-to-end technical ownership of a multi-system platform domain or complex cross-team engineering initiative • Deep hands-on experience with distributed processing, analytical or relational databases, production ETL, change-data capture, streaming or event processing, or backend and cloud systems handling large data volumes • Strong software engineering fundamentals and production proficiency in a backend or systems language • Deep experience using data-processing and platform libraries or frameworks • Experience crafting reusable abstractions, reviewing substantial changes, and debugging critical code paths • Strong SQL and data-modeling skills • Practical depth in query execution, incremental processing, schema evolution, consistency, analytical consumption, idempotency, replay, late-arriving data, partial failure, and cross-system correctness • Demonstrated skill diagnosing failures using logs, metrics, traces, query plans, profiles, and controlled experiments • Strong architectural judgment across reliability, performance, cost, security, compatibility, and maintainability • Experience guiding major migrations or architectural changes across teams without interrupting production service • Experience establishing automated testing, CI/CD, monitoring, alerting, rollback, incident response, and secure deployment practices • Deep experience with distributed data processing and lakehouse architectures • Experience operating distributed streaming or event-driven systems • Experience leading scaling, migration, or performance improvement of relational, distributed, time-series, object-storage, or searchable-content data systems • Background operating cloud infrastructure, container orchestration, workload schedulers, compute or GPU clusters, and fleet-scale telemetry • Experience defining and owning production adoption of agentic systems or workflow automation

🏖️ Benefits

• Equity • Comprehensive benefits package • Competitive salary