Senior Staff Data Engineer

Qualcomm

Confirmed live yesterday Trusted

Quick summary

Work type
On-site
Location
San Diego, CABoulder, CO
Salary
$158,400–$237,600 / yr
Posted
122 days ago
Freshness
Confirmed live yesterday
Closes
Nov 8, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $177k
This role $198k
$128k most similar roles pay here $249k

This role pays more than 67% of similar roles. Most pay $142,850–$211,200 — the shaded band above. At the midpoint, this role pays about $198k versus about $177k for comparable roles.

Based on 240 similar postings.

Employer

About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 623 open roles on FindRole.

Listed pay typically runs $148,300–$222,500 across 603 roles with salary data.

Most-posted roles

View all roles at Qualcomm

At a glance

TL;DR · Senior Staff Data Engineer

Data Engineer, Senior Staff joins the Information Technology Group to design, build, and operate a modern, scalable data platform using Databricks Lakehouse as its core foundation. This hands-on role involves developing reusable data frameworks, shared components, and standardized pipelines to support analytics, reporting, and downstream AI and machine learning use cases. The engineer will manage batch and streaming pipelines, implement automated data quality checks, and oversee infrastructure reliability through SLI/SLO monitoring. Key technical requirements include proficiency in Python, SQL, NoSQL databases, and experience with AWS services like IAM and networking. The role also requires expertise in Databricks features such as Delta Lake and Unity Catalog. Candidates must possess strong skills in data modeling, schema evolution, and cost optimization while ensuring security and governance across all shared data assets and automated workflows.

What does a Data Engineer earn in California?

Median $199800 from 35 postings across 19 companies.

See salary data

What you'll do

  • Design, build, and maintain scalable batch and streaming data pipelines using Databricks Lakehouse.
  • Develop reusable data engineering frameworks, libraries, and templates for ingestion, transformation, and validation.
  • Implement AI-based techniques to automate schema inference, quality checks, and self-healing pipeline mechanisms.
  • Establish standardized patterns for data modeling, pipeline orchestration, and governance across shared assets.
  • Monitor SLIs/SLOs and perform incident response to ensure platform reliability and performance.
  • Execute performance tuning and cost optimization strategies for cloud resources and workloads.
  • Contribute to architectural decisions, data standards, and technical guidance for junior engineers.

What we're looking for

  • Bachelor's degree in Computer Engineering, Computer Science, Information Systems, or a related field (or 9+ years of IT experience).
  • 7+ years of IT-related work experience.
  • 5+ years of experience with programming languages such as Java or Python.
  • 3+ years of experience with SQL or NoSQL databases.
  • 3+ years of experience with data structures and algorithms.
  • 8+ years of experience building and operating data platforms or distributed data systems.
  • Proven experience with Databricks Lakehouse, including Delta Lake and Unity Catalog.
  • Strong hands-on experience with AWS infrastructure, including IAM, networking, and multi-account setups.

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