Qualcomm
Data Platform Engineer, Senior Staff
$162K–$242K
San Diego, California · On-site · Senior Staff · Full-time · Posted Oct 27, 2026
- Experience
- 7+ years with a relevant Bachelor's degree, or 9+ years without one; also 5+ years programming, 3+ years with SQL or NoSQL databases and data structures and algorithms, 8+ years building and operating large-scale cloud platforms, and 5+ years in Data Platform, DevOps, SRE, or DataOps roles.
- Education
- Bachelor's degree in Computer Engineering, Computer Science, Information Systems or a related field, or 9+ years of IT-related work experience without a Bachelor's degree.
- Visa sponsorship
- Not eligible for Qualcomm immigration sponsorship.
About the job
Designs, builds, and operates Qualcomm’s Databricks-based data platform, with ownership of architecture, reliability, security, and cost optimization.
What you'll do
- Design and operate scalable data systems, Databricks workspaces, infrastructure, and end-to-end data pipelines.
- Build CI/CD and infrastructure automation; operate Amazon EKS and monitor platform reliability and data quality.
- Lead incident response, strengthen governance and security, and mentor engineers on platform standards.
What they ask for
- 7+ years of IT-related work experience with a relevant Bachelor's degree, or 9+ years without a Bachelor's degree.
- 5+ years programming experience; 3+ years with SQL or NoSQL databases and data structures and algorithms.
- 8+ years building and operating large-scale cloud platforms; 5+ years in Data Platform, DevOps, SRE, or DataOps roles.
- Expert AWS experience; hands-on Databricks Lakehouse, Terraform/Terramate, CI/CD, Python and Bash, Amazon EKS, and SLI/SLO experience.
Nice to have
- Experience with Acceldata, OpenTelemetry, or data observability tools; Fivetran Hybrid / HVR or enterprise ingestion tools.
- Experience with secret management, OPA, Sonar, data lineage or metadata tools, or Databricks serverless compute optimization.
Pay
$161,600.00 - $242,400.00 USD base salary
Tools
Databricks Lakehouse Platform, Unity Catalog, Delta Lake, MLflow, AWS, Terraform/Terramate, GitHub Actions, Jenkins
AI focus
Supports data pipelines for analytics and ML and maintains CI/CD pipelines for ML artifacts; no other AI work is specified.
Model-written summary · the original posting is authoritative