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Senior Team Manager, Cloud Data Platform Engineering

Job in Southlake, Tarrant County, Texas, 76092, USA
Listing for: Charles Schwab & Co
Full Time position
Listed on 2026-02-16
Job specializations:
  • IT/Tech
    Cloud Computing, IT Project Manager, Data Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Job Overview

Your opportunity

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together.

Schwab Technology Services enables the future of how clients manage their money by providing innovative and reliable technology products and services as part of our ongoing commitment to democratize access to investing and financial planning.

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.

Key Responsibilities
  • Platform Leadership & Service Enablement:
    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.
  • Data Services Development & Adoption:
    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.
  • Platform Operations & Reliability:
    Ensure high availability, performance, and operational excellence across core analytics platforms through strong SRE practices, incident management, capacity planning, and continuous improvement.
  • Cloud Modernization & Scale:
    Drive modernization of cloud‑native data platforms and services, incorporating automation, standardization, and reusable patterns to support growing user demand and evolving enterprise workloads.
  • Governance, Security & Compliance:
    Partner with security, risk, and compliance teams to ensure platforms and services meet regulatory requirements, enforce access controls, and align with enterprise governance standards.
  • Cross‑Team

    Collaboration:

    Work closely with application teams, enterprise data producers/consumers, Cloud Services, and external vendors to align roadmaps, manage dependencies, and deliver cohesive platform capabilities.
Operational Excellence
  • Monitoring & Observability:
    Establish and maintain robust monitoring, alerting, and operational metrics to proactively identify issues and improve platform stability and user experience.
  • Incident &

    Risk Management:

    Lead response to production incidents and operational risks, driving root‑cause analysis, remediation, and preventative controls.
  • Disaster Recovery & Business Continuity:
    Ensure disaster recovery and resilience strategies are defined, tested, and continuously improved for mission‑critical data platforms and services.
Leadership And Team Development
  • 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.
Collaboration And Influence
  • Strategic Partnerships:
    Build strong partnerships with internal stakeholders and external vendors to align platform development with…
Position Requirements
10+ Years work experience
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