Sr Manager, Cloud Engineer Lead

Your Opportunity

Schwab remains committed to providing increased visibility to career growth opportunities and job requirements. This posting announcement is part of increased transparency and while all qualified applicants will be reviewed and considered, this organization has a preferred candidate identified for this role. 

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 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 continuing to expand its Google Cloud-based Data & AI capabilities across the enterprise. The platform ecosystem now supports a growing portfolio of shared data, analytics, AI/ML, observability, self-service, and platform engineering capabilities across multiple Schwab enterprises, multi-tenant platforms, and application teams.

This senior individual contributor role will provide cross-platform technical delivery leadership across Cloud Data & AI Services and CDWP, while coordinating broader platform demand across CDWP, PAML, CLZ, SATP, OADIP, and related applications. The role will own integrated roadmap execution, delivery governance, dependency management, and cloud demand coordination across platform managers, technical leads, engineers, architects, central Public Cloud teams, and enterprise tenants.

The ideal candidate is a senior cloud engineering delivery lead who can operate at the intersection of technical platform execution, enterprise demand management, roadmap planning, stakeholder coordination, and operational readiness. This role requires the ability to understand complex Google Cloud platform capabilities, translate demand into executable delivery plans, manage dependencies across multiple teams, and drive predictable execution for critical firmwide data, analytics, and AI/ML enablement.

This is a high-impact opportunity to help scale Schwab enterprise cloud data and AI platform delivery model while improving speed, reliability, governance, and execution discipline across critical shared platforms.

Key Responsibilities:

Cross-Platform Technical Delivery Leadership

• Lead integrated technical delivery across Cloud Data & AI Services and CDWP, ensuring roadmap execution, dependency management, delivery sequencing, and release readiness across multiple platform workstreams.
• Coordinate execution across platform managers, technical leads, cloud engineers, architects, product partners, and enterprise customers to translate demand into clear delivery plans and measurable outcomes.
• Drive delivery governance for shared Google Cloud Data & AI capabilities, including prioritization, milestone tracking, risk management, dependency resolution, and stakeholder communication.
• Own cross-platform execution routines that improve visibility, accountability, decision-making, and delivery predictability across platform teams.
• Lead complex delivery efforts that span multiple Schwab enterprises, platform teams, applications, cloud services, security partners, and operational stakeholders.

CDWP Engineering Delivery and Tenant Enablement

• Lead delivery coordination for CDWP tenant provisioning, upgrades, platform enhancements, onboarding improvements, lifecycle changes, and enterprise enablement demand.
• Partner with CDWP engineering leads and platform managers to sequence work across infrastructure, platform services, data services, tenant readiness, controls, and supportability requirements.
• Improve repeatable delivery patterns for tenant onboarding, platform upgrades, environment coordination, service enablement, documentation, and production readiness.
• Coordinate customer and tenant-facing delivery discussions to clarify demand, align expectations, manage dependencies, and ensure platform work is delivered with appropriate quality and controls.
• Identify systemic delivery bottlenecks across CDWP execution and drive improvements through governance, standardization, automation opportunities, and better dependency management.

Cloud Data & AI Services Roadmap Execution

• Lead integrated execution for cloud services that support enterprise data, analytics, AI/ML enablement, self-service capabilities, observability, and platform automation.
• Coordinate roadmap delivery for new and expanding cloud services across multiple enterprises, ensuring technical readiness, adoption sequencing, operating model alignment, and support readiness.
• Partner with engineering teams to evaluate service delivery impacts across infrastructure, access patterns, cost, capacity, reliability, security, observability, and operational controls.
• Support delivery planning for AI-assisted capabilities and platform applications, ensuring dependencies are visible across engineering, architecture, security, operations, and customer teams.
• Drive disciplined execution of service expansion while maintaining predictable delivery, governance, reliability, and operational readiness.

Cloud Demand Coordination Across Data Platforms and Applications

• Coordinate cloud demand across CDWP, PAML, CLZ, SATP, OADIP, and related applications, ensuring platform needs are clearly articulated, prioritized, and aligned with central Public Cloud teams.
• Partner with central Public Cloud teams to manage demand intake, capacity dependencies, service readiness, cloud enablement needs, platform constraints, and delivery sequencing.
• Develop a consolidated view of cross-platform demand, risks, dependencies, and readiness needs across Schwab data platforms and applications.
• Ensure platform demand is translated into actionable work across cloud infrastructure, networking, IAM, service enablement, resiliency, observability, and operational readiness.
• Help reduce fragmented cloud demand management by creating consistent coordination patterns across data platforms and enterprise stakeholders. 

Technical Governance, Controls, and Operational Readiness

• Drive execution governance across delivery scope, technical dependencies, change readiness, risk management, controls, and production support expectations.
• Ensure platform delivery is aligned with enterprise standards for security, resiliency, operational readiness, auditability, change management, and supportability.
• Coordinate readiness reviews across platform releases, tenant onboarding, service changes, new capabilities, upgrades, and operational transitions.
• Partner with architecture, cybersecurity, operations, production support, and engineering teams to manage delivery risks and ensure platform changes are supportable at enterprise scale.
• Support continuous improvement of delivery controls, execution metrics, operational health indicators, and readiness practices across Cloud Data & AI Services and CDWP.

What you have

To ensure that we have fulfilled our promise of "challenging the status quo," this role has specific qualifications that successful candidates should have.

Required: 

Bachelor degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.

• 10+ years of experience in cloud platform engineering, infrastructure engineering, software engineering, data platform engineering, enterprise application engineering, or related technology engineering roles.
• 7+ years of experience delivering complex technology initiatives across enterprise platforms, shared services, cloud infrastructure, data platforms, or large-scale application ecosystems.
• 5+ years of experience in an enterprise data platform ecosystem, including interaction with ETL, data integration, BI/reporting, analytics, data science, operational reporting, and downstream data consumption patterns.
• 4+ years of experience with cloud platform delivery, preferably involving Google Cloud Platform services, shared cloud engineering capabilities, platform modernization, or enterprise cloud enablement.
• Experience leading technical delivery across multiple teams, including engineering managers, technical leads, platform engineers, architects, operations teams, product partners, and customer or tenant teams.
• Experience coordinating cross-platform roadmaps, delivery governance, dependency management, release readiness, risk management, and stakeholder communication.
• Experience supporting or leading delivery for multi-tenant data, analytics, AI/ML, or cloud platform services with shared infrastructure, platform services, onboarding patterns, access controls, and operational support expectations.
• Experience operating in production-oriented environments with expectations for change control, incident response, resiliency, observability, operational readiness, and audit/control alignment.

Required Technical Expertise

• Strong design-level expertise with Google Cloud services used for enterprise data, analytics, AI/ML, streaming, orchestration, security, networking, observability, and platform operations.
• Technical expertise with Google Cloud services such as BigQuery, Dataproc, Dataflow, Pub/Sub, Cloud Composer, Cloud Storage, IAM, VPC networking, Cloud Logging, Cloud Monitoring, and related platform services.
• Strong understanding of Infrastructure-as-Code practices, preferably Terraform, including reusable modules, controlled environment provisioning, access patterns, configuration management, platform lifecycle changes, and production deployment governance.
• Strong understanding of enterprise data platform patterns, including data ingestion, transformation, orchestration, data warehouse integration, platform services, analytics consumption, BI/reporting usage, and data science enablement.
• Strong understanding of cloud security and governance practices, including IAM, least-privilege access, network controls, vulnerability remediation, audit readiness, operational controls, and regulated enterprise delivery expectations.
• Ability to assess technical dependencies across cloud infrastructure, data platform services, application integrations, runtime environments, access models, networking, observability, and operational support models.
• Ability to convert complex technical demand into executable roadmaps, delivery milestones, dependency plans, readiness criteria, and leadership-facing execution updates. Required Leadership and Collaboration Skills
• Demonstrated ability to lead through influence across managers, engineers, architects, product partners, operations teams, and enterprise stakeholders.
• Strong delivery leadership skills with the ability to manage ambiguity, sequence complex work, resolve dependencies, frame risks, and drive decisions across multiple teams.
• Strong executive communication skills with the ability to summarize technical delivery status, risks, tradeoffs, and decisions clearly for senior stakeholders.
• Strong customer and tenant engagement skills, including demand clarification, expectation management, prioritization support, and delivery alignment.
• Ability to mentor engineers and delivery leads on roadmap planning, dependency management, execution governance, operational readiness, and stakeholder communication.
• Strong ownership mindset with the ability to drive cross-platform initiatives from intake through execution, readiness, adoption, and continuous improvement.

Preferred:

• Experience delivering or coordinating shared cloud data platforms, analytics platforms, AI/ML platforms, data science platforms, or internal platform services in a large enterprise environment.
• Experience with streaming, event-driven, or real-time processing patterns using technologies such as Pub/Sub, Dataflow, Kafka, or equivalent services.
• Experience coordinating centralized cloud demand across multiple platforms, product teams, application teams, or enterprise programs.
• Experience with SRE practices, observability dashboards, alerting models, incident management, capacity planning, reliability metrics, and operational health reporting.
• Experience supporting disaster recovery exercises, resiliency validation, recovery playbooks, operational readiness reviews, and continuous improvement of recovery procedures.
• Experience with CI/CD, GitHub Actions, Jenkins, automated testing, release automation, policy-as-code, or platform lifecycle automation.
• Experience with cloud cost optimization, capacity planning, workload placement, service adoption planning, and performance tuning for enterprise data or analytics platforms.
• Experience working in financial services or another highly regulated enterprise environment.
• Experience building delivery operating models, governance routines, roadmap dashboards, dependency maps, or executive-level delivery reporting for complex engineering portfolios.  

In addition to the salary range, this role is also eligible for bonus or incentive opportunities