Senior Data and Platform Engineer
NVIDIA AI · Orange County, CA · 3 wk ago
EngineeringFull-time
We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule headings only if content exists. We must not repeat job title. Remove boilerplate like Job ID, Job Category, Time Type, etc. Also remove EEO, equal opportunity, application instructions, etc. Keep substantive info.
We need to parse the posting.
Key sections:
- About the role: description of team, what they do, etc. Could be first paragraph: "NVIDIA’s DGX Cloud organization is seeking a Senior Data Engineer to become part of its data team! We develop the reliable data foundation that supports fleet health, capacity, utilization, cost, reliability, and operational decision-making throughout DGX Cloud. Our platform supports engineering, operations, finance, and product teams managing and expanding large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform. We develop the systems that transform distributed infrastructure telemetry and operational data into dependable, managed data products that support fleet health, capacity, utilization, cost, and operational decisions. We are seeking a hands-on, platform-minded engineer to build and evolve the systems that turn distributed infrastructure telemetry and operational data into reliable, governed data products. You will work across ingestion, transformation, data quality, platform architecture, security, observability, and self-service consumption to help make Navigator and the DGXC data platform a dependable source of truth."
That's about the role.
- Responsibilities: "What You'll Be Doing" bullet list. We need to extract each bullet as . The bullet list includes many sentences separated by periods? Actually it's a paragraph with sentences separated by line breaks? Let's extract each bullet as separate items:
Own systems end to end. For example, work from ambiguous customer and operational needs through architecture, implementation, deployment, observability, incident response, and ongoing support.
Construct data pipelines and products. Such as designing and maintain batch and streaming ingestion, transformation, reconciliation, and serving paths for fleet, capacity, utilization, cost, scheduling, and operational telemetry.
Build shared libraries, workflow and DAG or equivalent experience abstractions to evolve the data platform. Develop deployment tooling, data contracts, and paved-road patterns that improve team speed and safety.
Engineer reliable distributed workloads. As well as diagnose correctness and performance issues across applications, SQL engines, Spark jobs, storage systems, networks, and cloud services. Build for retries, idempotency, backfills, schema evolution, and partial failure.
Treat security as part of the build. For example, applying least privilege, service identities, secrets management, access controls, environment isolation, auditability, and safe operational practices throughout the system lifecycle.
Improve quality and operations: Establish automated tests, data-quality checks, lineage, freshness and completeness monitoring, actionable alerting, SLOs, and clear ownership.
Deliver consumption experiences. Such as making trusted data usable through well-modeled tables, APIs, automation, dashboards, and focused internal applications—not only through one-off queries.
Raise the engineering bar. Lead build reviews, communicate tradeoffs, mentor other engineers, and improve the team's architecture, testing, debugging, and operational practices.
We can treat each as a list item.
- Requirements: "What We Need To See" bullet list. Items:
BS or MS in Computer Science, Engineering, or a related field, or equivalent experience.
5+ years of experience building and operating production software, data platforms, backend infrastructure, databases, or distributed systems.
Strong software-engineering fundamentals and production proficiency in Python or another backend or systems language, with the ability and willingness to work primarily in Python and SQL.
Deep hands-on experience in at least one of the following areas: Distributed data processing using Spark or a comparable compute framework, Relational, distributed, or analytical database architecture and operation at scale, Production ETL, change-data-capture, streaming, or event-processing systems, Backend or cloud-platform systems that process, transform, or serve substantial data volumes, Strong SQL and data-modeling skills, including a practical understanding of query performance, schema evolution, incremental processing, consistency, and analytical consumption patterns.
Demonstrated ability to debug unfamiliar systems across multiple layers using logs, metrics, traces, query plans, profiles, and controlled experiments to find root causes.
Experience operating services or pipelines in a cloud or similarly complex production environment, including testing, CI/CD, monitoring, alerting, rollback, and incident response.
Working knowledge of secure platform development, including identity and access management, least privilege, secret handling, trust boundaries, and safe multi-environment deployments.
Ability to make sound architectural tradeoffs, own work through ambiguity, and communicate effectively with users, partner teams, and engineers from different fields.
A track record of learning unfamiliar technologies and domains and turning that learning into maintainable systems and reusable team practices.
Experience with AI agents and LLM-supported workflow automation, particularly as applied to engineering and operational activities.
- Skills: "Ways To Stand Out From The Crowd" bullet list. Items:
Experience with Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, Unity Catalog, or another modern lakehouse or distributed-compute platform.
Experience with Kafka or another streaming platform, change-data capture, event development, partitioning, consumer groups, offset management, or other high-volume event systems.
Experience with scaling, migrating, or performance-tuning relational, distributed, time-series, object-storage, or search-focused data systems, including Elasticsearch or OpenSearch.
Background working with AWS, Azure, GCP, Kubernetes, Slurm, compute clusters, GPU-accelerated infrastructure, or fleet-scale telemetry.
Experience developing agentic systems, LLM-enabled workflow automation, harness engineering, or dependable evaluation and operational tooling for AI agents.
- Benefits: The posting says "You will also be eligible for equity and benefits." That's vague but mentions benefits. It's not specific. According to rule: do NOT create Benefits section unless posting actually states them. It says "eligible for equity and benefits." That's a statement about benefits existing, but not specifics. Might be considered stating benefits exist. However rule: "never create Pay/Schedule/Benefits sections unless the posting actually states them." It does state benefits (eligible for equity and benefits). So we can include a Benefits section with that statement. But we should avoid filler like "not specified". We have a statement: "You will also be eligible for equity and benefits." That's substantive enough.
- Pay: The posting includes salary ranges: "Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 140,000 USD - 224,250 USD for Level 3, and 168,000 USD - 270,250 USD for Level 4." That's specific. So include Pay section with that info.
- Schedule: Not mentioned besides "Time Type Full time" but we removed that as metadata. No further schedule details. So we should not create Schedule section.
Now we need to output HTML fragment with headings for each section that has content.
We need to use
for each section that has content.
We need to use - for any list of duties/requirements/benefits, and
for prose.
Thus:
About the role
... prose ...
Responsibilities
- ...
...
Requirements
- ...
...
Skills
- ...
...
Benefits
You will also be eligible for equity and benefits.
Pay
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 140,000 USD - 224,250 USD for Level 3, and 168,000 USD - 270,250 USD for Level 4.
We should not include any other headings.
Make sure to preserve all substantive information. Ensure we didn't lose any details from About the role paragraph. Let's copy that paragraph exactly as in posting but maybe we can combine sentences. The About the role paragraph includes multiple sentences; we can keep as is.
Let's extract the About the role text:
"NVIDIA’s DGX Cloud organization is seeking a Senior Data Engineer to become part of its data team! We develop the reliable data foundation that supports fleet health, capacity, utilization, cost, reliability, and operational decision-making throughout DGX Cloud. Our platform supports engineering, operations, finance, and product teams managing and expanding large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform. We develop the systems that transform distributed infrastructure telemetry and operational data into dependable, managed data products that support fleet health, capacity, utilization, cost, and operational decisions. We are seeking a hands-on, platform-minded engineer to build and evolve the systems that turn distributed infrastructure telemetry and operational data into reliable, governed data products. You will work across ingestion, transformation, data quality, platform architecture, security, observability, and self-service consumption to help make Navigator and the DGXC data platform a dependable source of truth."
We need to keep exclamation mark etc.
Now Responsibilities list items: we need to ensure each bullet is a complete sentence as in posting. Let's copy each bullet exactly as they appear (maybe with minor punctuation). We'll produce - Own systems end to end. For example, work from ambiguous customer and operational needs through architecture, implementation, deployment, observability, incident response, and ongoing support.
Similarly for others.
Check each bullet:
1. Own systems end to end. For example, work from ambiguous customer and operational needs through architecture, implementation, deployment, observability, incident response, and ongoing support.
2. Construct data pipelines and products. Such as designing and maintain batch and streaming ingestion, transformation, reconciliation, and serving paths for fleet, capacity, utilization, cost, scheduling, and operational telemetry.
Note: "designing and maintain" maybe typo but keep.
3. Build shared libraries, workflow and DAG or equivalent experience abstractions to evolve the data platform. Develop deployment tooling, data contracts, and paved-road patterns that improve team speed and safety.
4. Engineer reliable distributed workloads. As well as diagnose correctness and performance issues across applications, SQL engines, Spark jobs, storage systems, networks, and cloud services. Build for retries, idempotency, backfills, schema evolution, and partial failure.
5. Treat security as part of the build. For example, applying least privilege, service identities, secrets management, access controls, environment isolation, auditability, and safe operational practices throughout the system lifecycle.
6. Improve quality and operations: Establish automated tests, data-quality checks, lineage, freshness and completeness monitoring, actionable alerting, SLOs, and clear ownership.
7. Deliver consumption experiences. Such as making trusted data usable through well-modeled tables, APIs, automation, dashboards, and focused internal applications—not only through one-off queries.
8. Raise the engineering bar. Lead build reviews, communicate tradeoffs, mentor other engineers, and improve the team's architecture, testing, debugging, and operational practices.
Now Requirements list items:
We need to capture each bullet exactly.
Let's list:
- BS or MS in Computer Science, Engineering, or a related field, or equivalent experience.
- 5+ years of experience building and operating production software, data platforms, backend infrastructure, databases, or distributed systems.
- Strong software-engineering fundamentals and production proficiency in Python or another backend or systems language, with the ability and willingness to work primarily in Python and SQL.
- Deep hands-on experience in at least one of the following areas: Distributed data processing using Spark or a comparable compute framework, Relational, distributed, or analytical database architecture and operation at scale, Production ETL, change-data-capture, streaming, or event
for prose. Thus:
About the role
... prose ...
Responsibilities
- ... ...
Requirements
- ... ...
Skills
- ... ...
Benefits
You will also be eligible for equity and benefits.
Pay
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 140,000 USD - 224,250 USD for Level 3, and 168,000 USD - 270,250 USD for Level 4.
We should not include any other headings. Make sure to preserve all substantive information. Ensure we didn't lose any details from About the role paragraph. Let's copy that paragraph exactly as in posting but maybe we can combine sentences. The About the role paragraph includes multiple sentences; we can keep as is. Let's extract the About the role text: "NVIDIA’s DGX Cloud organization is seeking a Senior Data Engineer to become part of its data team! We develop the reliable data foundation that supports fleet health, capacity, utilization, cost, reliability, and operational decision-making throughout DGX Cloud. Our platform supports engineering, operations, finance, and product teams managing and expanding large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform. We develop the systems that transform distributed infrastructure telemetry and operational data into dependable, managed data products that support fleet health, capacity, utilization, cost, and operational decisions. We are seeking a hands-on, platform-minded engineer to build and evolve the systems that turn distributed infrastructure telemetry and operational data into reliable, governed data products. You will work across ingestion, transformation, data quality, platform architecture, security, observability, and self-service consumption to help make Navigator and the DGXC data platform a dependable source of truth." We need to keep exclamation mark etc. Now Responsibilities list items: we need to ensure each bullet is a complete sentence as in posting. Let's copy each bullet exactly as they appear (maybe with minor punctuation). We'll produce