Databricks Lead (Staff IT Engineer)

Company: Qualcomm Incorporated Job Area: Information Technology Group, Information Technology Group > IT Engineering General Summary: The Databricks Lead (Staff IT Engineer) is a hands-on technical leader responsible for designing, building, and operating enterprise-scale Databricks solutions. This role drives platform adoption, AI-native development practices, machine learning enablement, AIOps automation, and cloud modernization initiatives. The individual will lead technical delivery, mentor engineers, establish engineering standards, and ensure highly scalable, secure, and intelligent data and AI platforms. This role requires full-time onsite work in San Diego, CA or Boulder, CO (5 days per week). This role is not eligible for Qualcomm immigration sponsorship.

Databricks Platform Leadership Design and implement scalable Lakehouse architectures using Databricks, Delta Lake, Unity Catalog, Workflows, and Serverless capabilities. Develop reusable platform frameworks, accelerators, and automation capabilities. Optimize platform performance, reliability, scalability, and cost efficiency. Drive platform modernization and cloud-native engineering best practices. AI-Native Development Promote AI-assisted software engineering using Claude Code, GenAI, and automation frameworks. Develop AI-powered engineering workflows to improve developer productivity and quality. Implement intelligent code generation, testing automation, root-cause analysis, and deployment optimization. Establish best practices for AI-enabled SDLC and platform operations. Machine Learning & AI Enablement Build and operationalize machine learning solutions using MLflow, Mosaic AI, Feature Engineering, and Model Serving. Support predictive analytics, anomaly detection, forecasting, and intelligent automation use cases. Implement model lifecycle management and MLOps practices. Collaborate with AI teams to enable enterprise AI workloads on Databricks. AIOps & Reliability Engineering Implement observability, monitoring, and automated incident management solutions. Build AI-driven operational insights for proactive issue detection and remediation. Improve platform reliability through self-healing automation and intelligent alerting. Drive reduction in operational toil through automation. Technical Leadership Lead technical design reviews and solution architecture discussions. Mentor engineers and establish coding, testing, and deployment standards. Drive engineering excellence through automation and reusable frameworks.

Experience 8–12 years of overall IT experience. 4–5 years of hands-on Databricks experience. Strong experience implementing enterprise cloud and AI platforms. Technical Skills Databricks Platform Delta Lake Unity Catalog MLflow Mosaic AI Python, SQL, Spark Databricks Workflows REST APIs GitHub  CI/CD Automation AIOps and Observability Platforms Generative AI tools and frameworks Leadership Competencies Technical mentoring Problem solving and innovation Cross-functional collaboration Continuous improvement mindset Strong communication skills Success Metrics Platform availability and reliability AI adoption across engineering teams Reduction in operational incidents Deployment automation maturity ML use-case adoption Cost optimization and utilization efficiency Minimum Qualifications: • 4+ years of IT-related work experience with a Bachelor's degree. OR 7+ years of IT-related work experience without a Bachelor’s degree. *Completed advanced degrees in a relevant field may be substituted for up to two years (Master’s = one year, Doctorate = two years) of work experience. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail  disability-accomodations@qualcomm.com  or call Qualcomm's toll-free number