Data Solutions, Staff Manager

Qualcomm Incorporated

Information Technology Group, Information Technology Group > IT Management

Staff Manager – Data Solutions will play a pivotal role in shaping the future of our enterprise data and analytics capabilities as part of a strategic and critical Enterprise Data Transformation (EDT) program. This role requires a visionary, hands‑on leader to drive the buildout of a modern, enterprise‑wide Lakehouse platform, ensuring reliability, scalability, security, and compliance, while enabling cutting‑edge BI, AI‑driven analytics, and data‑powered applications.

This role will lead a high‑performing team spanning data engineering, BI enablement, AI/advanced analytics, and application‑integrated data solutions, fostering a culture of engineering excellence, innovation, and operational rigor. The role will collaborate closely with cross‑functional teams (solution engineers, SMEs, application teams, and business stakeholders) to align data platforms, analytics, AI, and application development with business objectives.

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

• 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.
• 5+ years of supervisory or leadership experience.
• Completed advanced degrees in a relevant field may be substituted for up to two years (Master’s = one year, Doctorate = two years) of the general IT-related work experience.

• Define and lead the vision, strategy, and roadmap for enterprise data team, including Lakehouse, data warehouses, BI platforms, governance, data quality, observability, and semantic layers.
• Position data platforms as a strategic enabler for BI self‑service, AI/GenAI, and data‑driven applications, aligned with business and technology roadmaps.

• Lead core Data Engineering teams responsible for building reusable, scalable data pipeline frameworks from ingestion through analytics‑and AI‑ready datasets.
• Support diverse data patterns including batch, streaming, and micro‑batch processing, with built‑in governance and security.
• Drive migration from legacy data warehouses to a modern Lakehouse hub, embracing GenAI, automation, and low‑code/no‑code approaches to accelerate development velocity.

• 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.

• Enable AI/ML and GenAI use cases across analytics and applications, including natural‑language querying, predictive insights, and intelligent automation.
• Collaborate with data science, BI, and application teams to integrate AI outputs into dashboards, workflows, and business applications responsibly and at scale.

• Collaborate with application development teams to embed data services, analytics, and AI capabilities into enterprise applications.
• Enable data products, APIs, and integration patterns that support operational and analytical use cases across the enterprise.

• Collaborate with IT, business, and application teams using a product mindset to ensure platforms meet evolving business needs.
• Partner with global teams and vendors to ensure high‑quality, timely delivery.

• Stay actively involved in architecture, technical design, execution,…