Data Engineering Senior Team Manager
About The Position
Schwab Technology Services is advancing the next generation of data, analytics, and AI capabilities through modern, cloud-based platforms and scalable engineering solutions. As a Senior Manager, Data Engineering, you will lead the strategy, modernization, and delivery of enterprise data platforms that power analytics, reporting, and AI-driven insights across the firm. This role sits at the center of Schwab’s transformation—driving trusted, high-quality data delivery and enabling business teams to make faster, more informed decisions. You will shape and scale cloud-native data engineering capabilities by establishing reusable frameworks, automated pipelines, and resilient architectures that improve data quality, governance, and operational efficiency. Through close partnership with product, business, data science, risk, and security stakeholders, you will translate complex business needs into sustainable technical solutions that accelerate enterprise outcomes. Success in this role requires balancing strategic leadership with hands-on technical direction—modernizing legacy platforms, advancing automation and CI/CD practices, and embedding strong data governance, lineage, and compliance standards. You will also build and develop high-performing teams, fostering a culture of accountability, innovation, and continuous improvement while influencing executive stakeholders on data strategy, priorities, and outcomes.
Requirements
- Bachelor’s or master’s degree in Computer Science, Engineering, Information Systems, or related field
- 10+ years of experience in data engineering, data integration, analytics engineering, or related disciplines
- 5+ years of people leadership experience managing engineering teams and enterprise-scale programs
- Deep expertise in data architecture, ETL/ELT frameworks, and data warehousing
- Hands-on experience with cloud data platforms (e.g., Snowflake, BigQuery, GCP, AWS) and enterprise integration tools (e.g., Informatica, Talend, IDMC)
- Experience designing and delivering scalable batch and real-time data pipelines across hybrid environments
- Proven experience implementing data governance, data quality, metadata management, and lineage frameworks
- Demonstrated success leading large-scale modernization, migration, or platform transformation initiatives
- Strong understanding of Agile, DevOps, CI/CD, and automation practices
- Ability to align technical strategy to business outcomes with strong stakeholder engagement and executive communication skills
Nice To Haves
- Experience supporting AI/ML platforms, model lifecycle management, or enterprise AI enablement
- Familiarity with tools such as Vertex AI, Dataiku, or MLOps frameworks
- Experience enabling AI-driven or conversational analytics use cases
- Background in financial services or other highly regulated environments
- Experience leading enterprise cloud modernization initiatives
Responsibilities
- Lead the strategy, modernization, and delivery of enterprise data platforms.
- Shape and scale cloud-native data engineering capabilities by establishing reusable frameworks, automated pipelines, and resilient architectures.
- Improve data quality, governance, and operational efficiency.
- Translate complex business needs into sustainable technical solutions.
- Modernize legacy platforms.
- Advance automation and CI/CD practices.
- Embed strong data governance, data quality, metadata management, and lineage frameworks.
- Build and develop high-performing teams.
- Influence executive stakeholders on data strategy, priorities, and outcomes.
Benefits
- Eligible for bonus or incentive opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Manager
