Director, Retail Data Strategy & Analytics (PL)

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 we fully intend for the selected candidate to work on site in one of the specified locations.

Charles Schwab’s Retail organization is the firm’s primary business unit, serving millions of investors and supported by more than 13,000 employees worldwide. As part of Schwab’s move to a federated data and analytics operating model, analytics and insights teams that historically operated within Schwab Data are being embedded directly into the Retail business, increasing their proximity to decision-makers while upholding the consistency, governance, and risk standards expected of enterprise data practices.

To power this transition, we are establishing a new Retail data workspace and are seeking a Director of Retail Data Platform to own its operational health, support model, and readiness for the business. This hands-on leader will establish sustainable ways of working across Retail analytics and coordinate closely with enterprise partners. You will keep the environment reliable, secure, scalable, supportable, and audit-ready while enabling analysts to focus on insights rather than operations.

Success means keeping the Retail analytics environment reliable, secure, scalable, supportable, and audit-ready while helping teams adopt sustainable operating practices. Responsibilities span the following key areas:

Environment Ownership & Operational Excellence

• Own the environment’s operational health and business readiness, including Google Cloud workspace administration, orchestration and automation configuration and lifecycle, monitoring, maintenance, performance, and support.
• Establish the support model, service expectations, escalation paths, incident response, root-cause analysis, and production-support documentation.
• Manage asset lifecycles from onboarding and certification through maintenance, archival, and retirement.

Access, Security & Control Implementation

• Serve as EUC steward for the cross-Retail data domain and sub-domains; administer least-privilege access, reviews, attestations, and required asset, metadata, artifact, and records documentation.
• Partner with enterprise security, risk, governance, and platform teams to implement evolving standards and controls, remediate gaps, and support audits.

Proactive Platform & Data Planning

• Partner with Retail analytics leaders, data providers, platform owners, and enterprise teams to anticipate data, reporting, analytics, control, technology, and support needs.
• Maintain an environment roadmap, identify dependencies and risks early, and establish repeatable intake and onboarding patterns for new data, assets, teams, and capabilities.
• Work with Retail analytics leaders and Schwab Data partners to establish sustainable patterns for bringing trusted operational data into the warehouse and making it analytics-ready as well as guiding analytics leaders on platform and operational implications while they retain ownership of business needs and priorities.
• Manage shared-data hygiene and lifecycle, implement enterprise acquisition and curation patterns, enable the Retail semantic layer, and support migration from Schwab Data-owned marts into the Retail data workspace.

Operating Model, Automation & Release Management

• Define how Retail teams develop, test, document, deploy, and maintain production assets, with clear ownership, approvals, controls, escalation paths, and readiness criteria.
• Move teams from legacy automation and orchestration to modern firm systems, and automate recurring reporting and processes to improve speed, reliability, scale, and consistency.
• Monitor adoption and partner with team leaders to close gaps and improve maturity.

Knowledge Transfer, Enablement & Continuity

• Onboard teams and establish practical standards, playbooks, process documentation, training, and self-service resources.
• Train analytics leaders and backup administrators; establish backup coverage and continuity plans; clarify self-service, centralized-support, and escalation responsibilities to reduce key-person dependency.

Cross-Functional Coordination & Enterprise Partnership

• Coordinate across Retail, Schwab Data, risk and supervision, and source-system partners to align plans, communicate impacts, manage dependencies, and resolve issues.
• Act as Retail Analytics’ primary Schwab Data liaison, represent operational needs, communicate enterprise changes, and coordinate requirements and prioritization for new enterprise data assets.
• Help Retail implement and scale within enterprise standards while enterprise teams retain ownership of firmwide strategy, architecture, governance, controls, and platform direction.

What you have

Required Qualifications

• 15+ years of experience leading data platforms, data management, business intelligence, analytics operations, or analytics delivery in a complex enterprise.
• Experience owning or administering data and analytics environments, including cloud platforms, monitoring, performance, access, controls, release management, and production support.
• Demonstrated success establishing scalable operating models, standards, ownership, documentation, support practices, and asset lifecycles.
• Ability to anticipate needs, build roadmaps, identify dependencies and risks early, and coordinate execution and issue resolution across business, data, technology, platform, security, risk, governance, and control partners.
• Experience establishing repeatable data-onboarding and asset-operationalization patterns with data providers, warehouse and platform teams, and source-system owners.
• Experience with data governance, access attestations, metadata, control implementation, audit readiness, playbooks, runbooks, training, knowledge transfer, and continuity planning.
• Experience automating and orchestrating data pipelines and recurring reporting, including peer review, release management, error handling, monitoring, quality management, and scheduling controls.
• Working knowledge of how analysts use relational and unstructured data for statistical analysis, reporting, and visualization.
• Experience with cloud and analytics technologies such as Google Cloud, BigQuery, semantic-layer platforms, SQL, GitHub, Control-M, SSIS, Informatica, Python, or similar tools.
• Experience using AI in the development lifecycle or enabling data environments for AI-enabled analytics.
• Self-starter able to balance hands-on operations with planning, enablement, and stakeholder coordination. Financial-services experience, relevant advanced degrees or credentials, and consulting experience are preferred.

Preferred Qualifications

• Bachelor’s degree in statistics, data science, mathematics, economics, computer science, business analytics, or a related field, or equivalent practical experience.