Qualcomm is seeking a Staff Data Engineer to design, build, and operate a modern, scalable data platform with Databricks Lakehouse as a core foundation. The role emphasizes building reusable data frameworks, shared platform components, and standardized pipelines to support analytics and advanced use cases, including AI and machine learning. This hands-on position requires full-time onsite work in San Diego, CA, and focuses on reliability, governance, and intelligent automation. The engineer will have meaningful ownership across various aspects of data engineering and contribute to architectural decisions.

• 5+ years of IT-related work experience with a Bachelor's degree in Computer Engineering, Computer Science, Information Systems, or a related field, or 7+ years of IT-related work experience without a Bachelor's degree.
• 3+ years of work experience with programming languages such as Java or Python.
• 3+ years of work experience with SQL or NoSQL databases.
• 3+ years of work experience with data structures and algorithms.

• Design, build, and maintain scalable batch and streaming data pipelines.
• Develop reusable data engineering frameworks, libraries, and templates for data ingestion, transformation, validation, and publishing.
• Establish standardized patterns for data modeling, transformations, and pipeline orchestration.
• Implement end-to-end data workflows from raw ingestion to curated analytical datasets.
• Leverage AI-based techniques to automate and optimize data engineering workflows.
• Define and monitor SLIs/SLOs for data pipelines, frameworks, and platform availability.
• Participate in incident response, on-call rotations, and post-incident reviews.
• Drive adoption of standardized data frameworks, automation patterns, and best practices across teams.

• Qualcomm offers competitive compensation, annual bonuses, stock programs, comprehensive healthcare coverage, retirement plans, wellness programs, parental leave, flexible work options, and professional development opportunities.