Senior Data Engineer

Nvidia

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
CATXSanta Clara, CA
Salary
$168,000–$270,250 / yr
Employment
Full-time
Posted
8 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $164k
This role $219k
$102k $288k
below market most similar roles pay here above market

This role pays more than 82% of similar roles. Most pay $126,800–$201,437 — the blue band above. At the midpoint, this role pays about $219k versus about $164k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

Most-posted roles

View all roles at Nvidia

At a glance

TL;DR · Senior Data Engineer

The Senior Data Engineer joins the Digital Marketing Operations team to build shared data infrastructure powering customer engagement, campaign intelligence, and marketing analytics. You will own a key data domain, architecting and evolving batch and streaming pipelines that ingest and transform customer behavioral signals, audience definitions, and consent records into governed data products. Responsibilities include leading cross-functional initiatives, mentoring junior engineers, and enforcing privacy-by-design requirements like GDPR and PIPL compliance. You will utilize Python, Java, or Golang, along with SQL, Apache Spark, and workflow orchestration tools like Airflow. The role involves managing cloud data warehouses, object storage, and lakehouse architectures using Apache Iceberg. You will solve complex problems regarding identity resolution, audience segmentation, and data lineage to ensure reliable, scalable, and privacy-compliant marketing technology operations.

What does a Data Engineer earn in California?

Median $187700 from 41 postings across 21 companies.

See salary data

What you'll do

  • Own a key data domain including pipelines, data products, audience services, and consumer teams.
  • Architect and implement batch and streaming pipelines to ingest and transform customer behavioral and campaign data.
  • Build reliable systems using distributed processing frameworks, workflow orchestration tools, and cloud data warehouses.
  • Develop and evolve shared data quality frameworks and engineering standards to improve pipeline reliability.
  • Lead production incident investigations to establish root causes and implement preventive improvements across distributed systems.
  • Embed privacy and compliance by design, including GDPR/PIPL controls, data minimization, and auditable lineage.
  • Establish robust data models, semantics, and serving interfaces to deliver trusted data assets to marketing consumers.
  • Provide technical leadership through architecture reviews and hands-on mentorship of junior engineers.

What we're looking for

  • 8+ years of relevant industry experience with a Bachelor's degree or equivalent experience.
  • Master's degree or equivalent in Computer Science, Engineering, or a related field.
  • Sustained record of designing, implementing, and operating production data pipelines, data platforms, or distributed data systems.
  • Proficiency in Python and one or more modern programming languages such as Java or Golang with strong SQL fundamentals.
  • Deep hands-on experience with distributed data processing frameworks like Apache Spark and cloud-managed ETL services.
  • Experience building and operating production pipelines with workflow orchestration tools such as Airflow or equivalent.
  • Experience with cloud data platform services, including object storage, cloud data warehouses, and managed transformation services.
  • Experience with data lake and lakehouse architectures, including open table formats such as Apache Iceberg.
  • Experience with MarTech stacks and B2C customer data at scale (preferred).
  • Experience designing and operating high-throughput, fault-tolerant streaming systems at scale (preferred).

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