Data Solutions, Staff Manager

Company:

Qualcomm Incorporated

Job Area:

Information Technology Group, Information Technology Group > IT Management

General Summary:

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).

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.

• 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.

Key Responsibilities

Vision and Strategy

• 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.

Data Engineering

• 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.

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.

AI & Advanced Analytics Enablement

• 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.

Application & Data Product Enablement

• 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.

Cross‑Functional Collaboration

• 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.

Hands‑On Leadership with Engineering Mindset

• Stay actively involved in architecture, technical design, execution, troubleshooting, and delivery, providing hands‑on guidance to accelerate outcomes.

Challenge Status Quo

• Drive innovation and continuous improvement by challenging legacy processes, introducing modern engineering practices, and adopting emerging technologies.

Required Experience & Qualifications

• 15+ years of IT experience in the Data, Analytics, BI, AI, or Application Development domain with a Bachelor’s degree.
• 7+ years of people and delivery leadership experience, managing technical teams.
• 3+ years of experience working with senior leadership, leading modernization of data platforms, BI, analytics, AI, and operations.
• Strong hands‑on experience with AWS and Databricks‑based data platforms.
• Solid hands‑on experience in Data Engineering, Data Modeling, BI/Analytics enablement, and AI‑ready data solutions.
• Demonstrated ability to drive end‑to‑end ownership, from strategy through execution.
• Passion for exploring emerging technologies, including GenAI and automation, and delivering Proofs of Concept (POCs).
• Ability to work independently and collaborate effectively with business, application, and cross‑functional teams.

Additional Qualifications

• 7+ years of IT experience with a Bachelor’s degree OR 9+ years without a Bachelor’s degree.
• 4+ years in leadership roles managing projects or programs.
• 15+ years of experience in data management, data engineering, BI, analytics, or data science, with 7+ years leading data modernization and DW/Lakehouse migrations.
• Strong hands‑on expertise with Lakehouse Medallion architecture, data engineering, operations, and governance.
• Proven implementation experience with platforms such as Databricks, Fivetran, Collibra, Acceldata, AWS, and cloud‑based BI and GenAI solutions (e.g., ThoughtSpot, Tableau Cloud).
• Deep knowledge of end‑to‑end DevOps and release management, from Git integration through deployment.
• Strong passion for building reusable data engineering frameworks and GenAI‑enabled agentic co‑development for accelerated delivery.
• Ability to build and scale data operations teams with modern observability and monitoring capabilities, supporting 24x7 operations.
• Experience with machine learning, artificial intelligence, and predictive analytics is a plus.
• Excellent leadership, communication, and collaboration skills in a global, hybrid delivery model.
• Strong problem‑solving, strategic thinking, and proactive execution mindset.
• Proven track record of leading strong technical teams and collaborating with data engineers, architects, BI developers, analysts, data scientists, and application teams.

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EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

Pay range and Other Compensation & Benefits:

$177,500.00 - $266,300.00

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm.  We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus).  In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link.

If you would like more information about this role, please contact Qualcomm Careers.