Your OpportunityAt 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). This role is expected to be in the office 4 days a week.
The Sales, Service, Marketing Technology (SSMT) organization is seeking a
Data Engineering, Senior Manager to lead a team of engineers responsible for building and evolving scalable data solutions that power insight driven decisions across Sales, Service, and Marketing platforms.
In this role, you'll combine people leadership, technical depth, and strategic thinking to shape our data engineering vision and deliver high impact solutions in a fastmoving, collaborative environment. You'll partner closely with cross functional stakeholders to turn complex data into reliable, actionable insights that support business growth and customer outcomes.
We're looking for a leader who enjoys developing talent, navigating ambiguity, and continuously improving how data is designed, delivered, and used across the organization.
Key Responsibilities:- Lead, coach, and develop a diverse team of software and data engineers, fostering a culture of collaboration, learning, and continuous improvement. The total team includes employees and on employees, upwards of around 40 individuals.
- Create an environment where engineers can do their best work through clear priorities, meaningful feedback, and growth opportunities
- Partner with product, architecture, analytics, and business teams to deliver enterprise scale data solutions aligned to business needs
- Define and advance a clear data engineering strategy that supports organizational goals and longterm scalability
- Guide the design, development, and optimization of data pipelines, data models, and data architecture for analytics, monitoring, and reporting
- Balance delivery, quality, and sustainability by managing capacity, timelines, and technical tradeoffs
- Champion modern data engineering practices, tools, and technologies to improve reliability, performance, and speedtovalue
- Ensure strong data governance, quality, and reliability standards are embedded into day to day engineering practices
- Lead teams across a mix of fulltime employees, contractors, offshore partners, and third-party vendors
What you haveTo ensure that we fulfill our promise of "challenging the status quo," this role has specific qualifications that successful candidates should have:
Required Qualifications:- 12+ years of experience in data engineering, including 5+ years in people leadership roles with accountability for hiring and onboarding, performance management, talent development, compensation planning, and building high-performing engineering teams.
- Architected enterprise ETL/ELT frameworks leveraging distributed processing, orchestration, and metadata-driven patterns to enable scalable and reusable data pipelines.
- Executed complex platform-to-platform data migrations, addressing data modeling differences, performance tuning, backward compatibility, and parallel run strategies.
- Transitioned monolithic and tightly-coupled legacy data systems to modern, decoupled, and resilient architectures aligned with cloud and data-platform best practices.
- Hands-on expertise with data integration tools such as Informatica IICS, PowerCenter, or Spring Batch.
- Strong experience working with relational (Oracle, SQL Server, PostgreSQL, or MySQL) and NoSQL databases (Mongo).
- Advanced SQL skills and experience with enterprise data modeling.
- Working knowledge in at least one modern programming language such as Python or Java.
- Experience building and supporting streaming or event-driven data pipelines (e.g., messaging platforms, Kafka, Pub/Sub).
- Working knowledge of data governance, data quality, and data lifecycle management practices.
- Experience enabling analytics and visualization platforms such as Tableau or Power BI through well-designed data models and pipelines.
- Bachelor's degree in Computer Science, Mathematics, or a related field, or equivalent practical experience.
Preferred Qualifications:- Experience supporting Salesforce platforms from a data ingestion or extraction perspective.
- Background in financial services or highly regulated environments.
- Experience designing or operating data platforms in a public cloud environment, such as Google Cloud Platform (GCP).
- Experience leading or enabling AI-assisted development practices, including code generation, automated testing, pipeline validation, or design acceleration.
Applicants must be currently authorized to work in the United States on a full-time basis without employer sponsorship.
In addition to the salary range, this role is also eligible for bonus or incentive opportunities
