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QU

IT Technical Lead

qualcomm
San Diego, United Statesfull_timeVerifiedPosted 20 Apr 2026
💰 $252,600/yr($168,400/yr$252,600/yr)

About the role


Company:

Qualcomm Incorporated

Job Area:

Information Technology Group, Information Technology Group > IT Engineering

General Summary:

Technical lead will play a critical role in shaping the future of our data capabilities as part of strategic and critical Enterprise Data Transformation (EDT) program. We're seeking a visionary, hands-on leader to drive the building out of a modern enterprise-wide lake house with scalable, reliable and business intuitive data architecture for supporting self-service capabilities across Data & Analytics solutions.

This role requires full-time onsite work in San Diego, CA (5 days per week).

Minimum Qualifications:

• 8+ years of IT-related work experience with a Bachelor's degree.
OR
10+ years of IT-related work experience without a Bachelor’s degree.

Key Responsibilities:

Vision and Strategy:  Define and lead the vision, strategy, roadmap for data solutions(Data warehouses, governance, data quality, application development, enterprise planning and observability etc.), aligning with business objectives and technological advancements to enable data solutions as the strategic enabler for AI

BI, Analytics & Self‑Service Enablement

  • Establish and lead BI and Analytics Centers of Excellence (CoEs), enabling governed self‑service analytics through semantic layers, certified KPIs, dashboards, and reporting solutions.

  • Partner with business stakeholders to drive analytics adoption, from ideation through production and scale, using modern cloud BI and AI‑augmented analytics tools.

Agentic AI & Intelligent Automation

  • Design and implement agentic AI workflows, where autonomous or semi‑autonomous agents orchestrate data access, ML inference, decision logic, and actions.

  • Build multi‑step agent pipelines that combine rules, ML models, and reasoning components to solve complex business problems.

  • Integrate agentic systems with enterprise data, ML models, and applications to enable intelligent automation and decision support.

Databricks Application Development

  • Design and develop Databricks‑native applications, including notebook‑based apps, interactive dashboards, and parameterized data/ML workflows.

  • Enable data products, APIs, and integration patterns that support operational and analytical use cases across the enterprise

  • Ensure Databricks apps meet performance, security, governance, and usability standards.

Traditional Machine Learning & Analytics

  • Design, develop, and deploy traditional machine learning models, including regression, classification, clustering, time‑series forecasting, and anomaly detection.

  • Perform feature engineering, model selection, training, validation, and performance tuning on large‑scale enterprise datasets.

  • Apply sound statistical and ML best practices to ensure model robustness, explainability, and business relevance.

Governance & Security: Enforce data governance policies, access controls, and compliance using tools like Unity Catalog or AWS Lake Formation.

Technical Leadership & Influence

  • Serve as a technical authority in traditional ML, agentic AI, and Databricks application patterns.

  • Influence architectural decisions, best practices, and technical standards across teams.

  • Mentor peers and raise the bar on ML rigor, engineering quality, and production readiness.

Stakeholder Collaboration: Serve as the primary liaison between business units and technical teams to translate business requirements into technical roadmaps.

Preferred Qualifications:

  • 14+ years of IT-related work experience in Data and Analytics domain with a Bachelor's degree.

  • 7+ years of enterprise data modelling experience.

  • 3+ years of work experience in a role requiring interaction with senior leadership, leading modernization of Data platforms.

  • Strong functional knowledge across Sales, Marketing, Customer Support, Supply Chain, Finance and other corporate functions

  • Deep hands-on technical understanding in building complex data models for supporting various analytics needs

  • Co

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Company

qualcomm

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