Manager, Data Engineering

Your Opportunity

Schwab remains committed to providing increased visibility to career growth opportunities and job requirements. This posting announcement is part of increased transparency and while all qualified applicants will be reviewed and considered, this organization has a preferred candidate identified for this role. 

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).

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.​

We’re seeking a Data Engineer who will design and deliver production-grade GenAI applications, enhancing the client journey and driving tangible business value. You’ll collaborate closely with architects, engineers, and business leaders to align solutions with Schwab’s strategic goals, and mentor junior team members—cultivating best engineering practices and a culture of continuous learning.  

In this pivotal role, you’ll not only advance technical standards and solve complex challenges but also lead rapid iterations from concept to production. You will bring curiosity, creativity, and technical depth to help shape the next era of AI at Schwab, with a special emphasis on reliability, monitoring, observability, and orchestration across products. Your work will be critical in maintaining high-performance, production-grade AI solutions that support decision-making and deliver consistent value.  

• Design, build, & optimize Generative AI applications that drive measurable business impact and enhance client experiences. You’ll lead the development of robust data pipelines and prompt engineering workflows, enabling efficient model iteration & performance tuning. 
• Champion best practices in reliability, monitoring, and observability across AI systems, ensuring scalable and actionable reporting.  
• Collaborate with cross-functional teams to align solutions with enterprise strategy and technical standards.  
• Mentor and coach junior engineers, fostering strong practices and continuous learning.  
• Lead by example in solving complex technical challenges and driving rapid iteration from concept to deployment.  
• Implement and maintain monitoring, alerting, and incident response frameworks to ensure system health and reliability.  
• Advance engineering standards, focusing on operational excellence and quality across all deliverables.

What you have

To ensure that we have fulfilled our promise of "challenging the status quo," this role has specific qualifications that successful candidates should have.

Required:

• 5+ years of data engineering experience, 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. 
• 5+ years developing scalable workflows and data pipelines that interface with large and complex datasets. 
• 3+ years designing and implementing solutions utilizing Artificial Intelligence components such as NLP, LLMs, or machine learning techniques. 
• Bachelor’s degree in Computer Science, Data Engineering, Mathematics, Analytics, or related field. 
• 2+ years working hands-on with containers and cloud-native platforms

Preferred:

• Strong 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