Data Engineer, Senior Staff

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
• ▹Leverage AI-based techniques to automate and optimize data engineering workflows (schema inference, data quality checks, self-healing)
• ▹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
• ▹Drive performance tuning and cost optimization
• ▹Partner with analytics, application, and platform teams
• ▹Mentor junior engineers

Requirements

• ▹7+ years of IT-related work experience with a Bachelor's degree in Engineering, Computer Science, or Information Systems (or 9+ years without one)
• ▹5+ 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 and libraries
• ▹Strong hands-on AWS experience, including IAM, networking, and multi-account setups
• ▹Proven experience with Databricks Lakehouse, including Delta Lake and Unity Catalog
• ▹Strong proficiency in Python for framework development and automation

Nice to have

• ▹Experience building internal data platforms or enablement frameworks
• ▹Experience supporting AI/ML teams as platform consumers
• ▹Experience with data observability and monitoring tools
• ▹Experience with enterprise ingestion tools (Fivetran, HVR)
• ▹Experience with data lineage or metadata management
• ▹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
• ▹Highly competitive benefits package

About the company

Qualcomm IT's Data Engineering team builds a modern, scalable data platform on Databricks Lakehouse to support analytics, reporting, and AI/ML use cases.