Senior Data Engineer, Platform

🔥 5 minutes ago

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

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

💵 $168k - $270.3k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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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 addressing scale, reliability, performance, security, compatibility, and cost • Lead technical delivery of complex cross-team initiatives • Translate unclear requirements into architectures and interfaces, coordinate implementation, write essential code, resolve 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, libraries, workflow/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 root causes, drive durable resolution, and implement preventive improvements • Drive engineering standards for testing, data quality, reconciliation, lineage, SLOs, observability, secure identities, least privilege, release readiness, and auditable deployments • Establish data models, semantics, ownership boundaries, and serving interfaces • Provide tables, APIs, automation, dashboards, and internal applications for trusted DGX Cloud data access • Provide technical leadership through architecture and build reviews, mentorship of senior engineers, and evidence-based tradeoff resolution

🎯 Requirements

• 8+ 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 record of personally 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 with 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 • 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 production safeguards and engineering practices adopted by multiple teams, including automated testing, CI/CD, monitoring, alerting, rollback, incident response, and secure deployment • Deep experience with distributed data processing and lakehouse architectures, or equivalent large-scale database/data-processing platforms • Experience operating distributed streaming or event-driven systems, including partitioning, consumer behavior, flow control, replay, delivery guarantees, and schema evolution • Experience scaling, migrating, or improving performance 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, focusing on evaluation, permissions, observability, failure recovery, and measurable improvements

🏖️ Benefits

• Highly competitive salaries • Comprehensive benefits package • Equity • Benefits for you and your family