
Pioneering accelerated computing and AI
Manager, Data and AI Engineering
We are looking for a Manager of Data & AI Engineering who combines deep technical expertise with strong delivery leadership and people management. This role will drive the build-out of our next-generation autonomous data intelligence platform for Supply Chain Operations — from identifying high-impact opportunities to architecting, building, and productionize solutions that deliver measurable business value. The ideal candidate brings hands-on experience in architecture and engineering while demonstrating the ability to manage a high-performing team. This person will partner with business collaborators, translate operational challenges into data and AI solutions, and deliver at pace.
What you'll be doing:
-
Design and build scalable data and AI platforms using Databricks, AWS, and modern cloud-native engineering patterns.
-
Deliver robust ETL/ELT, streaming, and CDC pipelines using technologies such as Spark, Kafka, Delta Lake, and AWS-native services.
-
Enable delivery of AI-powered use cases including RAG applications, AI agents, tool-calling workflows, and data-driven web apps.
-
Design data models using Star Schema, Snowflake Schema, and Data Vault patterns appropriate to the use case — optimizing for analytical query performance, data governance, and extensibility.
-
Implement data quality frameworks, observability, alerting, and monitoring to ensure pipeline integrity and production reliability.
-
Build the data foundation for GenAI, agentic AI, and advanced analytics initiatives, including RAG pipelines, vector search, knowledge graphs, and multi-agent orchestration patterns
-
Partner with product, business, analytics, and AI collaborators to translate requirements into secure, scalable, and production-ready solutions.
-
Oversee resource planning, prioritization, project execution, and delivery across multiple concurrent initiatives, and mentor engineers, grow technical capability across the team, and develop a culture of accountability, innovation, and continuous improvement.
-
Provide hands-on technical leadership across architecture, design reviews, implementation guidance, and production readiness, and handle the full lifecycle of data engineering projects — from discovery and planning through execution and production rollout.
What we need to see:
-
Master's or Bachelor's degree in Computer Science or Information Systems, or equivalent experience
-
10+ overall years in Data Engineering, Software Engineering, or web application development, with at least 3+ years specifically in a leadership or engineering management role.
-
Willingness to Code: You are still a builder at heart. You are excited to spend your time writing code, prototyping, and building production systems alongside your team.
-
AWS Proficiency: Intimate knowledge of the AWS ecosystem, including Amazon S3, EC2, IAM, Lambda, and API Gateway.
-
Agentic AI & LLM Mastery: Proven experience operationalizing Large Language Models (LLMs) into autonomous agents that can plan, use tools, and implement multi-step workflows.
-
Databricks Mastery: Proven deep expertise in Apache Spark, Py Spark, Delta Lake, and Databricks Workflows. Hands-on experience scaling Unity Catalog is highly preferred.
Ways to stand out from the crowd:
-
Active Databricks Certifications (e.g., Data Engineer Professional, Generative AI Engineer Associate).
-
Active AWS Certifications (e.g., Certified Data Engineer – Associate or Solutions Architect – Professional).
-
Background in managing multi-functional teams that blend data engineers with front-end and back-end software developers.
-
Knowledge of supply chain business processes for Plan, Make, Deliver & Services
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 26, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
전체 조회수
0
전체 지원 클릭
0
전체 Mock Apply
0
전체 스크랩
0
비슷한 채용공고

Data AI Engineering Specialist (Hybrid), Director
Morgan Stanley · Montreal, Quebec, Canada

Data Manager
TotalEnergies

Data Engineering Lead - Client Technology
EY

Python Data Engineer, Vice President
Citigroup · JACKSONVILLE, Florida, United States of America

Lead Data & Analytic Engineer
Walt Disney · London, United Kingdom
NVIDIA 소개

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
직원 수
Santa Clara
본사 위치
$4.57T
기업 가치
리뷰
10개 리뷰
4.4
10개 리뷰
워라밸
2.8
보상
4.5
문화
4.2
커리어
4.3
경영진
3.8
78%
지인 추천률
장점
Cutting-edge technology and innovation
Excellent compensation and benefits
Great team culture and collaboration
단점
High pressure and expectations
Poor work-life balance and long hours
Fast-paced environment leading to burnout
연봉 정보
79개 데이터
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
7개 리포트
$170,275
총 연봉
기본급
$130,981
주식
-
보너스
-
$155,480
$234,166
면접 후기
후기 5개
난이도
3.0
/ 5
면접 과정
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
최근 소식
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
reddit/blind
·
NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
reddit/blind
·
NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
reddit/blind
·
NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
reddit/blind
·