2 days ago
Base Salary
$248k - $391k/yr
Responsibilities
- Define the architecture, system boundaries, interfaces, technical roadmap, and engineering standards for ingestion, processing, storage, and data serving.
- Lead delivery across platform engineers, data producers, and data consumers from ambiguous requirements through production adoption.
- Build and operate reusable batch and streaming ingestion capabilities with APIs, change data capture, streams, database connectors, files, orchestration, retries, backfills, and recovery.
- Establish shared identifiers, data contracts, consistent data models, automated quality checks, certification capabilities, dataset ownership, and compatibility standards.
- Guide dataset cataloging, lineage, governed access, and discovery capabilities for people and AI agents.
- Create shared libraries, reference implementations, deployment automation, and self-service workflows that reduce onboarding effort and manual toil.
- Own production readiness and reliability standards, including SLOs, testing, observability, runbooks, rollback, recovery, secure deployment, and incident response.
- Lead investigations and migrations across pipelines, applications, SQL engines, Spark, storage, networks, and cloud services.
- Mentor senior engineers and technical leads, lead design reviews, resolve technical disagreements, and advise leadership on priorities, risks, and investments.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- More than 16 years of progressively responsible experience developing and operating production software, data platforms, databases, or distributed systems.
- Sustained experience defining technical strategy and architecture for shared platforms spanning multiple teams, with accountability for delivery, adoption, and production outcomes.
- Extensive hands-on experience with distributed data processing, analytical databases, production ETL, streaming systems, or backend platforms handling substantial data volumes.
- Strong software engineering fundamentals and production proficiency in Python or another backend or systems language, with willingness to work primarily in Python and SQL.
- Deep SQL and data modeling expertise, including query execution, incremental processing, schema evolution, consistency, idempotency, replay, late-arriving data, partial failure, and correctness across system boundaries.
- Experience establishing production practices adopted by multiple teams, including CI/CD, data validation, observability, incident response, secure deployment, and recovery.
- Demonstrated ability to lead complex production investigations and major migrations using logs, metrics, traces, query plans, profiles, and controlled experiments.
- Demonstrated success influencing technical direction across organizational boundaries and developing engineers for broader technical responsibilities.
- Preferred experience with Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, Unity Catalog, self-service data publishing, cataloging, lineage, data contracts, certification systems, Kafka, comparable streaming systems, and production agentic systems.
Benefits
- Competitive base salary of $248,000–$391,000 plus equity and benefits.
- Comprehensive benefits package for employees and their families.
- Applications will be accepted at least until November 14, 2026; the posting represents an existing vacancy.
Tech Stack
Categories
Data Engineering
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.