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Schwab is transforming enterprise data and analytics through a secure, scalable, and self-service Google Cloud–based ecosystem. As part of this evolution, the Schwab Google Data & Analytics (SGDA) ecosystem is expanding its Core Cloud Data Platforms and Data Services capabilities to support firmwide analytics, AI/ML, and next-generation data products. We are seeking a seasoned Senior Manager for our Cloud Data Platforms and Data Services to lead the engineering, operations, and evolution of Schwab’s foundational analytics platforms and shared data services. This role will oversee cloud data platforms serving thousands of analytics users and data scientists while driving the development of reusable, governed data and AI services consumed by multiple enterprise teams. This is an opportunity to lead at scale, shaping how data platforms and services are built, operated, and adopted across Schwab in a highly regulated environment.
Job Responsibility:
Lead the engineering and operational strategy for Schwab’s core cloud data platforms and shared data services, ensuring they are reliable, secure, scalable, and aligned to enterprise analytics and AI adoption needs
Oversee the design, development, and lifecycle management of shared data and AI services that enable self-service analytics, machine learning, and generative AI use cases across multiple enterprise domains
Ensure high availability, performance, and operational excellence across core analytics platforms through strong SRE practices, incident management, capacity planning, and continuous improvement
Drive modernization of cloud-native data platforms and services, incorporating automation, standardization, and reusable patterns to support growing user demand and evolving enterprise workloads
Partner with security, risk, and compliance teams to ensure platforms and services meet regulatory requirements, enforce access controls, and align with enterprise governance standards
Work closely with application teams, enterprise data producers/consumers, Cloud Services, and external vendors to align roadmaps, manage dependencies, and deliver cohesive platform capabilities
Establish and maintain robust monitoring, alerting, and operational metrics to proactively identify issues and improve platform stability and user experience
Lead response to production incidents and operational risks, driving root-cause analysis, remediation, and preventative controls
Ensure disaster recovery and resilience strategies are defined, tested, and continuously improved for mission-critical data platforms and services
Cultivating Leadership: Encourage leadership development within the team by delegating authority and fostering an environment conducive to growth and innovation
Mentorship and Professional Growth: Provide ongoing mentorship, promoting a culture of learning and adaptation. Support team members in achieving professional certifications and mastering new technologies
Team Dynamics and Engagement: Enhance team collaboration and morale through regular feedback, recognition, and team-building exercises. Ensure a diverse and inclusive team environment that values open communication and shared success
Strategic Partnerships: Build strong partnerships with internal stakeholders and external vendors to align platform development with broader organizational goals. Advocate for technological advancements that drive business value
Continuous Performance Optimization: Systematically analyze platform operations to identify bottlenecks and inefficiencies. Implement solutions that enhance service delivery and user satisfaction
Requirements:
Bachelor’s or master’s degree in computer science, engineering, or a related field
Minimum of 5+ years in technology leadership roles managing complex, large-scale cloud platforms and engineering teams
Ownership and Operation of multi-tenant, shared cloud platforms (Google Cloud preferably)with expertise in services like BigQuery, Vertex AI, Dataproc, Composer, Dataflow, Pub Sub, Cloud Functions, Cloud Build, Cloud Run, Cloud Scheduler
Experience with traditional AI/ML platforms like Dataiku or AWS Sagemaker and Generative AI services/LLMs like Google Vertex AI, Microsoft Open AI
Strong understanding of security protocols, Identity & Access Management (IAM), and compliance frameworks relevant to the financial services industry
Skilled in using Terraform and other IaC tools to manage infrastructure deployments efficiently
Proven ability to mentor and lead diverse teams, fostering an environment of growth and innovation
Experience managing teams of platform engineers in a shared services or platform model
Excellent at diagnosing and resolving complex issues swiftly and effectively
Exceptional communication abilities, capable of effectively negotiating and influencing across multiple levels of the organization
Nice to have:
Experience with major cloud platforms such as AWS, Azure, and GCP
Experience developing and managing cross-enterprise platforms in financial services can be a key differentiator
What we offer:
401(k) with company match and Employee stock purchase plan
Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions