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.
Schwab Technology Services enables the future of how clients manage their money by providing innovative and reliable technology products and services as a part of our ongoing commitment to democratize access to investing and financial planning.
As part of Schwab's AI Engineering & Operations team, you will be building the next generation Generative AI solutions that shape the future of technology at Schwab. In this role, you will contribute to the development and deployment of AI products that are instrumental in driving data-informed business decisions and elevating client experiences. You'll collaborate across teams to deliver scalable, secure, and high-performing AI systems that align with Schwab's innovation strategy and operational goals.
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:- 8+ years of ETL engineering experience, with 4+ years as a hands-on senior engineer
- 5+ years designing and developing scalable data pipelines that integrate with large, complex datasets across diverse environments including structured and unstructured data formats. Must be proficient in working with various API types (REST, SOAP, Graph), handling authenticated data sources, and implementing complex extraction procedures.
- 5+ years building and maintaining production-grade data pipelines across multiple data delivery modes (streaming, batch) and data classification protocols (internal, confidential, PII).
- 5+ years of experience with data governance and risk frameworks, including metadata management and classification.
- Bachelor's degree in Computer Science, Data Engineering, Mathematics, Analytics, or related field.
- 3+ years working hands-on with containers and cloud-native applications.
Preferred Qualifications:- Strong ETL/data engineering fundamentals and experience across the tech stack.
- Commitment to quality-driving high standards including writing tests at all levels.
- Strong written and verbal communication skills to clearly convey ideas and feedback.
- Mentoring junior engineers and supporting their technical growth through code reviews and guidance.
- Mindset of continuous learning and improvement.
- Ability to solve complex problems with ambiguous or incomplete data in distributed systems.
- Demonstrated business domain knowledge relevant to previous products.
- Curiosity about new technologies and processes, proactively sharing knowledge and seeking improvement.
- Experience with Python preferred but not required.
- Master's or advanced degree in Computer Science, Data Engineering, Mathematics, Analytics, or related field.
In addition to the salary range, this role is also eligible for bonus or incentive opportunities.
Applicants must be currently authorized to work in the United States on a full-time basis without employer sponsorship.
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