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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. We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).
Schwab Technology Services (STS) enables how clients manage their money by delivering innovative, reliable, and scalable technology that supports equitable access to investing and financial planning.
Within Schwab Data’s Data Services team, you will play a meaningful role in shaping the next generation of cloud and AI capabilities that power enterprise-scale analytics. You will apply your expertise to design and build core cloud service modules on Google Cloud that support AI/ML and data platforms, enabling resilient, scalable, and secure solutions.
In this role, you will collaborate closely with architects, site reliability engineers, and engineering leaders to implement modern cloud service engineering practices, improve delivery velocity, and influence enterprise standards. Your work will directly contribute to advancing Schwab’s cloud data strategy while solving complex, high-impact engineering challenges.
This is an opportunity to deepen your expertise in cloud platform engineering, automation, and AI-enabled data services while contributing to a highly visible and evolving space within Schwab.
What you have
Required Qualifications
Hands-on experience developing and enabling cloud service modules for Google Cloud Platform (GCP) environments (e.g., BigQuery, Dataflow, Dataproc, Composer, Vertex AI), with focus on scalability and operational resilience
Experience building and maintaining CI/CD pipelines to support automated testing, deployment, and lifecycle management
Strong understanding of cloud infrastructure provisioning and management to support secure, multi-tenant, enterprise-scale environments
Experience applying engineering, security, and compliance standards, including governance, audit readiness, and risk controls
Demonstrated ability to troubleshoot and optimize distributed platform components, including resolving dependencies, performance issues, and breaking changes
Experience using Infrastructure-as-Code tools (e.g., Terraform) to automate environment configuration and deployment
Proven ability to collaborate cross-functionally with architects, SRE teams, and engineering partners to support platform reliability and consistency
Preferred Qualifications
Experience developing reusable platform accelerators, templates, or SDKs that enable faster onboarding and delivery across teams
Familiarity with AI/ML platform integration patterns and supporting advanced analytics or generative AI use cases
Knowledge of FinOps practices and cloud cost optimization strategies
Strong communication and influencing skills to align stakeholders and drive adoption of platform standards
Ability to proactively identify technical risks and recommend scalable, compliant solutions in complex or regulated environments
In addition to the salary range, this role is also eligible for bonus or incentive opportunities.