Senior Manager, Digital Analytics

As a Senior Enterprise Analytics Developer, you will focus on delivering well-governed, production-ready analytics that enable consistent, data-informed decision-making across the organization. You will enable analytics use-cases by preparing high-quality, standardized datasets that integrate with evolving platforms, improving consistency while reducing rework and downstream reconciliation. Your work will directly support how teams understand client behavior, operational performance, and cross-enterprise outcomes around Schwab.com and the mobile app. Your role is at the intersection of enabling a specific business unit's data & analytics use cases while building scale. Day to day, this means you'll engage with business partners to understand their needs, iteratively develop data assets to fuel their local analytics, and consider how the reusable data asset can scale across needs of other business units at Schwab.

You will also ensure analytics assets are documented, auditable, and resilient to support regulatory expectations in a financial services environment. You will contribute to the evolution of shared analytics capabilities by improving consistency, scalability, and governance across domains, helping drive more reliable and connected decision-making across the enterprise. Success in this role requires strong problem-solving, collaboration across teams, and the ability to deliver local value with speed while staying aligned to enterprise-level governance & standards. 

• 8-10+ years of experience designing and developing production-ready analytics data assets using SQL, python, and orchestration frameworks (alteryx, control-M, airflow, etc) in an enterprise data environment 
• An undergraduate degree in Engineering, Information Management, Finance, Mathematics or related field 
• Must be a motivated self-starter who can work independently and seeks out opportunities to work collaboratively with others in an energetic, fast-paced environment 
• Must have the ability to manage concurrent projects at different stages of completion 
• Must be able to explain complicated subject matters to others across the business that are less connected to an initiative and/or are less technically oriented 
• Experience applying data modeling practices to support scalable reporting across shared datasets 
• Experience partnering with business stakeholders to translate requirements into analytics solutions, and drive an analytics and data curation roadmap 
• Understanding of financial services data, including client behavior, transactional flows, and/or operational metrics 
• Strong focus on data quality, documentation, and maintainability 
• Ability to work across teams and navigate ambiguity in complex problem spaces 

• Experience with semantic or metrics layers and reusable analytics frameworks 
• Exposure to digital or product analytics and behavioral data 
• Familiarity with enterprise data platforms and evolving analytics ecosystems 
• Interest in AI-driven analytics and automation capabilities