> Markdown version of [/jobs/ext/3472091-databricks-lead-staff-it-engineer](https://www.wearedevelopers.com/jobs/ext/3472091-databricks-lead-staff-it-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Databricks Lead (Staff IT Engineer)

- **Company:** Qualcomm
- **Location:** San Diego, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $116,800.0 - $175,200.0
- **Contract:** Permanent contract
- **Skills:** Unity 3d, Artificial Intelligence, Application Frameworks, Automation of Tests, Mobile Application Development, Cloud Engineering, Code Generation, Continuous Integration, Github, Data Intelligence, Python (Programming Language), Machine Learning, Systems Development Life Cycle, Reliability Engineering, Software Engineering, SQL Databases, Cloud Platform System, Feature Engineering, Apache Spark, Generative AI, HybridCloud, Data Lakes, AI Platforms, Deployment Automation, Machine Learning Operations, Restful APIs, Serverless Computing, Databricks
- **Published:** September 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=d369b6bfc51ccb3b

## About the Role

* 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.

## Description

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., 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.