Data and Platform Engineer

🔥 2 minutes ago

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

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

💵 $200k - $322k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🏗️ Platform Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 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

• Own a major Navigator data platform component and its roadmap, including architecture, interfaces, technical goals, and evolution • Anticipate capacity, compatibility, and operational needs over a multi-year horizon • Lead technical delivery across teams by clarifying requirements, breaking down work, managing dependencies and risks, and keeping stakeholders aligned • Build batch and streaming ingestion, transformation, reconciliation, and serving processes for fleet, capacity, utilization, cost, scheduling, and operational telemetry • Establish stable data models and agreements as sources, consumers, and scale evolve • Direct creation and adoption of libraries, workflow/DAG abstractions, deployment tools, and standard implementation approaches • Lead complex production investigations across pipelines, applications, SQL engines, Spark, storage, networks, and cloud services • Define and implement testing, data-quality, reconciliation, lineage, SLO, and release-readiness standards • Partner with security and infrastructure teams on trust boundaries, service identities, least privilege, secrets, environment isolation, and auditability • Deliver well-modeled tables, APIs, automation, dashboards, and focused internal applications • Guide design reviews, mentor engineers taking on larger ownership, and resolve technical disagreements • Partner with leadership on priorities and explain how technical investments support DGXC objectives

🎯 Requirements

• BS or MS in Computer Science, Engineering, or a related field (or equivalent experience) • At least 12+ years of equivalent experience • Sustained record of building and operating production software, data platforms, databases, or distributed systems • Experience owning a major component or complex project from requirements and architecture through release and ongoing operation • Ability to outline technical plans, establish objectives, assign design and implementation tasks, and guide delivery with little supervision • Practical experience with distributed processing using Spark or similar systems, databases, production ETL, change-data capture, streaming, event handling, or backend and cloud platforms managing large data volumes • Strong software-engineering fundamentals and production proficiency in Python or another backend or systems language • Ability and willingness to work primarily in Python and SQL • Experience designing reusable abstractions, reviewing substantial changes, and implementing and debugging critical code paths • Strong SQL and data-modeling skills, including query execution, incremental processing, schema evolution, consistency, and analytical consumption • Ability to reason about idempotency, replay, late-arriving data, partial failure, and correctness across system boundaries • Experience leading complex investigations involving multiple components and teams • Ability to use logs, metrics, traces, query plans, profiles, and controlled experiments to establish root cause and prevent recurrence • Demonstrated architectural judgment balancing reliability, performance, cost, security, compatibility, and maintainability • Experience leading significant migrations or architectural changes while preserving production service • Experience establishing testing, CI/CD, monitoring, alerting, rollback, incident response, and secure deployment practices • Proven success influencing technical decisions without official authority and advancing workflow improvements across related teams • Ability to simplify complex issues and communicate decisions and delivery risks clearly • Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, or Unity Catalog expertise is advantageous • Kafka or comparable streaming systems experience is advantageous • Experience with Elasticsearch or OpenSearch is advantageous • Experience with Kubernetes, Slurm, cloud infrastructure, and fleet telemetry across AWS, Azure, GCP, or other providers is advantageous • Experience building production agentic systems or agent harnesses is advantageous

🏖️ Benefits

• Equity • Benefits