Qualcomm
IT Program Manager, Staff - Enterprise Data Transformation
$169K–$254K
San Diego, California · On-site · Staff · Full-time · Posted Sep 25, 2026
- Experience
- 8+ years required; 10+ years preferred.
- Education
- Bachelor’s degree in Information Technology, Information Systems, Computer Science, Data Science, Engineering, Business, or a related field; master’s degree preferred.
- Visa sponsorship
- Not eligible for visa sponsorship.
About the job
Leads Qualcomm’s multi-year global enterprise data transformation, establishing the Enterprise Data Hub as a governed platform for trusted data products, analytics, applications, and advanced technology solutions.
What you'll do
- Directs cross-functional delivery from strategy and planning through platform development, migration, deployment, adoption, and benefits realization.
- Establishes program governance, roadmaps, budgets, dependencies, risk management, executive reporting, and partner oversight.
- Coordinates data architecture, Databricks implementation, governance, legacy modernization, organizational change, and operating-model transition.
What they ask for
- Bachelor’s degree in a related field.
- 8+ years of program or project management experience, including large, complex, global technology or business transformation programs.
- Experience leading a significant enterprise data platform, data modernization, analytics, cloud, or related transformation through multiple lifecycle phases.
- Experience with modern cloud data platforms and technologies, enterprise data management, data integration, migration, and multi-million-dollar budgets.
Nice to have
- 10+ years of program management experience, including multi-year global transformations.
- Experience with Databricks capabilities, public-cloud data services, AI/ML solutions, or relevant certifications.
Pay
$169,200.00 - $253,800.00 USD (pay range; salary/base pay)
Tools
Databricks, Delta Lake, Unity Catalog, Lakeflow, Databricks SQL, MLflow, AWS, Microsoft Azure
AI focus
Enables governed enterprise data for AI and machine-learning solutions, including generative AI, retrieval-augmented generation, conversational analytics, intelligent agents, model operations, and intelligent automation; AI experience is preferred.
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