Staff Data Engineer

Stack

Responsibilities

• ▹Design, build and maintain scalable batch and streaming data pipelines
• ▹Develop reusable data engineering frameworks, libraries and templates for 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
• ▹Apply AI-based techniques to automate and optimize data engineering workflows (schema inference/evolution, automated data quality checks, anomaly detection, self-healing pipelines)
• ▹Ensure data quality, reliability and performance across pipelines and shared frameworks
• ▹Support downstream consumers such as analytics, reporting and AI/ML teams
• ▹Define and monitor SLIs/SLOs for data pipelines, frameworks and platform availability
• ▹Participate in incident response, on-call rotations and post-incident reviews
• ▹Implement security, compliance and data governance controls across shared data assets
• ▹Drive performance tuning and cost optimization, including automated resource-utilization recommendations
• ▹Partner with analytics, application and platform teams to identify common data needs and platform gaps
• ▹Mentor junior engineers and provide technical guidance

Requirements

• ▹Bachelor's degree in Computer Science, Computer Engineering, Information Systems or related field + 5+ years of IT-related experience, OR 7+ years of IT-related experience without a degree
• ▹3+ years of programming experience (e.g., Java, 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 designing reusable data engineering frameworks, libraries or platform components
• ▹Strong hands-on AWS experience (IAM, networking, multi-account setups)
• ▹Proven experience with Databricks Lakehouse, including Delta Lake and Unity Catalog
• ▹Strong proficiency in Python for framework development, data processing and automation
• ▹Required to work onsite in San Diego, 5 days a week
• ▹Not eligible for Qualcomm immigration sponsorship

Nice to have

• ▹Familiarity with secret management tools (Vault or similar)
• ▹Experience optimizing Databricks performance and cost
• ▹Experience working with globally distributed teams

Soft skills

What we offer

• ▹Annual discretionary bonus program
• ▹Opportunity for annual RSU grants
• ▹Competitive benefits package

About the company

Qualcomm's IT Data Engineering team builds an enterprise-scale data platform on Databricks Lakehouse that powers analytics, reporting and AI/ML use cases.