Senior Level Cloud Data Engineer Jobs
Senior level cloud data engineer jobs put experienced engineers in charge of cloud data architecture decisions, pipeline ownership, and the cross-functional teams that deliver production-grade data systems at scale. Roles are distributed across on-site, remote, and hybrid settings in Technology & Software, Artificial Intelligence, and Electronics & Hardware, with employers like Google, Snowflake, and NVIDIA hiring at this level now.
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Join the NVIDIA GeForce NOW cloud team that allows users to play high-quality PC games on various devices, without the need for a dedicated gaming PC or console. NVIDIA's GeForce NOW service is built on top of our GPU technology, including our proprietary GPU architectures and software optimizations allowing efficient and high-quality experience even at high resolutions and fps and at industry leading low latencies.
Our team is building the Diagnostic, Prescriptive and AI-augmented Analytics solutions that encompass processing, visualization, anomaly detection, root cause and predictive modeling for the benefit of millions of our end users. Our active projects include real-time forecasting of demand, constraint-optimized capacity allocation, dynamic prescriptions per session, Customer Onboarding and Voice of Customer Analytics, targeted Customer Outreach campaigns based on Customer Retention modeling, effective personalized diagnostic recommendations, LLM Chatbot. You will wield the power of Data and AI to help globally deliver a best-in-class cloud computing/streaming performance and experience. Our technology stack relies on industry standard components and tools (Python, R, Pandas, JupyterLab, Spark, SQL, Databricks, MLFlow, Delta Lake, Grafana, Kibana, Kubeflow, Elyra, Kubernetes, Gitlab, CI/CD, MLOps, Kafka, SQS, Kubernetes)
What you'll be doing:
Provide Technical Leadership to the team of Data Scientists and Engineers working on global deployment at scale of GPU Compute services.
Work with Leadership and Stakeholders to understand top level requirements, build a tech roadmap, design solutions and guide the team to deliver results.
Acquire and apply domain knowledge of the product and platform to lead the design, implementation, and deployment of AI/ML based solutions for generating actionable insights and real-time prescriptive analytic pipelines to drive optimal outcomes for production services.
Build and Deploy real time and scalable solutions for real time User Diagnostics, LLM Chatbot, dynamic Suspicious Activity Detection, User feedback based clustering and alerting and LLM based Actionable Insight Generation solutions for Engineering And Management.
Improve productivity of the org by wrangling petabytes of data using statistical/AI/ML/LLM models to provide actionable and real time insights.
Leverage pioneering Forecasting models and Constraint Optimization solvers to improve capacity management and deliver server efficiency and end-user latency.
Leverage innovative ML/AI predictive models with explainability for User Retention/Churn and designing outreach campaigns.
Build innovative multi-agent self-learning Harnesses for improving engineering productivity for analytics and deployments.
What we need to see:
Master’s/PhD or equivalent experience in Data Science, Statistics, Mathematics, Physics, Operations Research or related quantitative field
15+ years of software experience for large-scale and reliable production deployments and 8+ years of proven experience in Statistics/AI/ML
Hands-on expertise in programming languages like Python, SQL, Java and modeling frameworks like Scikit-learn, Pytorch, TensorFlow for large projects.
Experience with common tools for data storage and processing (e.g. Spark, Pandas, Delta Lake) including drilling into problems of running large scale software in a big network.
Excellent verbal and written communication skills to convey rich data insights to non-Technical and Technical Stakeholders.
An outstanding track record of successful past projects, as a lead, related to the research and application of data science at scale.
Experience of User Retention Modeling, LLMs, Time Series Forecasting or Operations Research is a plus.
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and versatile people in the world working with us, and our engineering teams are growing fast in some of the most impactful fields of our generation: AI, Data Engineering, Data Science. If you're a creative engineer who enjoys autonomy and shares our passion for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 248,000 USD - 379,500 USD.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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. #deeplearningSee All 41 Senior Level Cloud Data Engineer Jobs
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Who's Hiring
- Google6
- Snowflake4
- NVIDIA2
- Pure Storage2

- Guidehouse2G
Top Industries Hiring
- Technology & Software24
- Artificial Intelligence8
- Electronics & Hardware4
- Investment & Asset Management3
- Manufacturing2
Senior Level Cloud Data Engineer Jobs: Frequently Asked Questions
How do I get a senior level cloud data engineer job?
Employers at this level look for engineers who have owned end-to-end data platform decisions, not just contributed to them. Strong candidates demonstrate experience designing scalable pipelines on major cloud platforms, leading migrations or architectural overhauls, and mentoring junior engineers. Hands-on depth with orchestration tools, data modeling, and cost optimization, paired with a history of driving measurable outcomes, sets candidates apart from mid-level applicants.
Which companies hire senior level cloud data engineers?
Companies hiring senior level cloud data engineers right now include Google, Snowflake, and NVIDIA, based on current listings on Migrate Mate as of July 2026. Hiring at this level covers large enterprises building out centralized data platforms and high-growth organizations scaling their analytics infrastructure to support business-critical decisions.
Are there remote senior level cloud data engineer jobs?
Yes, remote availability is strong at this level. About 30% of senior level cloud data engineer openings are remote or hybrid as of July 2026, reflecting how cloud-native work naturally accommodates distributed teams. Senior engineers with deep platform expertise are in enough demand that many employers extend flexible arrangements to attract and retain them.
What makes a cloud data engineer role senior level?
Senior level cloud data engineer roles are defined by ownership and scope. Engineers at this level architect solutions rather than implement specifications, make platform and tooling decisions with long-term implications, and are accountable for reliability and performance at scale. They also mentor and guide junior and mid-level engineers, contribute to technical roadmaps, and collaborate directly with data science, analytics, and product stakeholders to shape how data flows across the organization.
Which industries hire the most senior level cloud data engineers?
Senior level cloud data engineer roles concentrate in Technology & Software, Artificial Intelligence, and Electronics & Hardware, based on current listings on Migrate Mate as of July 2026. These sectors generate the data volume, compliance requirements, and infrastructure complexity that make experienced cloud data engineering expertise a core business need rather than a supporting function.