Manager, Data Engineering (DAFgiving360)

Your Opportunity

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).

Applicants must be currently authorized to work in the United States on a full-time basis without employer sponsorship.

DAFgiving360 is a mission-driven nonprofit dedicated to expanding philanthropic giving and helping donors make a greater impact in their communities. As a Manager, Data Engineer, you will play a critical role in advancing DAFgiving360's Foundation360 strategy by designing, building, and evolving trusted data solutions that enable analytics, operational efficiency, automation, and future AI capabilities. Working across Data, Technology, Analytics, Governance, Product, and business teams, you will develop scalable data platforms, improve data reliability and accessibility, and simplify complex data ecosystems to support informed decision-making. This role combines hands-on engineering expertise with strategic thinking to deliver modern data capabilities, strengthen data governance and quality practices, and drive continuous platform improvement. Success requires strong collaboration, problem-solving, and the ability to influence technical direction while building data products that are secure, scalable, and trusted across the organization.

What you have

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Analytics, or a related field, or equivalent experience.
• 7+ years of experience in data engineering, data architecture, analytics engineering, software engineering, or related technical disciplines.
• Advanced experience with SQL and data modeling, including designing scalable, business-aligned data structures.
• Experience developing and supporting ETL/ELT pipelines, data integration solutions, and orchestration workflows.
• Experience working with cloud-based data platforms and modern warehouse, lake, or lakehouse environments.
• Experience supporting production data systems, including monitoring, incident response, and operational reliability.
• Knowledge of data governance, metadata management, data lineage, and data quality practices.
• Demonstrated problem-solving, communication, documentation, and stakeholder partnership skills.
• Proven ability to collaborate cross-functionally and influence technical outcomes without direct authority.
• Applicants must be currently authorized to work in the United States on a full-time basis without employer sponsorship.

Preferred Qualifications

• Experience with Google Cloud Platform, BigQuery, and cloud-native data engineering solutions.
• Advanced experience with Python for data processing, automation, and engineering framework development.
• Experience implementing data quality, observability, and automated testing practices.
• Experience with governed self-service analytics and medallion/lakehouse architecture patterns.
• Experience with Git, CI/CD pipelines, and modern software engineering delivery practices.
• Experience supporting data foundations for advanced analytics, automation, machine learning, or AI initiatives.

In addition to the salary range, this role is eligible for bonus or incentive opportunities.