Your OpportunityAt Schwab, we're driven by a shared purpose: helping investors reach their financial goals with confidence. Within Schwab International Services, you'll play a critical role enabling data-informed decisions that support global growth, operational excellence, and strong risk and regulatory outcomes. You'll join a collaborative, inclusive environment where diverse perspectives are valued, continuous learning is encouraged, and your work has clear business impact.
This role sits within International Business Operations and leads analytics delivery for International Services-modernizing reporting, improving data quality, and empowering business partners with trusted, timely insights.
As Senior Manager, Data Analytics, you will lead the delivery of reporting, analytics, and data solutions supporting International Services. You will partner closely with business, operations, and risk stakeholders to define meaningful KPIs, evolve manual reporting into scalable data assets, and deliver insights that inform strategy, prioritization, and execution.
This is a hands-on leadership role requiring both strategic thinking and deep analytical execution. You will influence outcomes through strong partnership and technical expertise, without direct people management responsibility.
What You'll Do (Key Responsibilities)
- Partner with business and operations leaders to define success measures, translate business questions into analytical requirements, and deliver actionable insights
- Modernize recurring Excel-based reporting into scalable, automated datasets and dashboards
- Design, build, and maintain curated data models and data pipelines using SQL and Python
- Develop and publish trusted, user-friendly dashboards and self-service analytics in Tableau and/or Power BI
- Establish and maintain practical reporting and dashboard governance, including data quality checks, refresh schedules, documentation, and access controls
- Deliver timely ad hoc analysis and executive-ready insights to support strategic and operational decisions
- Collaborate across analytics, data engineering, and business teams to drive standardization, reuse enterprise data assets, and improve end-to-end data quality
- Communicate complex technical concepts in clear, business-relevant terms
What you haveSkills and Capabilities (What You Bring)- Ability to translate ambiguous business needs into clear, testable analytical deliverables
- Strong analytical problem-solving skills and comfort working with complex datasets
- Proficiency in SQL for building reusable datasets and performant queries
- Experience using Python and/or R for data analysis, automation, and data manipulation
- Capability to design, publish, and maintain dashboards with clear metric definitions and documentation
- Knowledge of data governance practices that improve trust, transparency, and scalability
- Strong stakeholder partnership skills, including the ability to influence without formal authority
- Ability to balance strategic thinking with hands-on execution
- Clear, concise written and verbal communication skills
- Comfort operating in evolving environments while maintaining focus and delivery discipline
Required Qualifications- 5+ years of experience in data analytics, business intelligence, data engineering, or a closely related field with increasing scope and ownership
- 3+ years of experience building and publishing dashboards using Tableau and/or Power BI
- 2+ years of hands-on experience developing and automating data pipelines or ETL/ELT workflows
- Advanced experience with SQL and relational data environments
- Experience using Python and/or R for analysis and automation
- Strong Excel capabilities, including improving and automating manual reporting processes
Preferred Qualifications- Bachelor's degree in Business, Finance, Management Information Systems, Computer Science, Analytics, Mathematics, or equivalent practical experience
- Experience supporting international, multi-region, or regulated financial services environments
- Familiarity with version control and collaborative development practices for analytics assets
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