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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). 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.
Job Responsibility:
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
Requirements:
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.
Applicants must be currently authorized to work in the United States on a full-time basis without employer sponsorship.
Nice to have:
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.
What we offer:
401(k) with company match and Employee stock purchase plan
Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions