Charles Schwab Recruitment Program 2026 | Hiring Associate – Software Development & Engineering

Qualifications

Required Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field (or equivalent practical experience).
• 2 years of software engineering experience (including internships, co-ops, undergraduate research, or substantial project work).
• Proficiency in at least one general-purpose programming language (e.g., Python, Java, C#, or similar) and comfort learning new technologies quickly.
• Working knowledge of data fundamentals: relational data concepts, writing SQL queries, and designing/debugging ETL/ELT-style data transformations.
• Understanding of core software engineering practices such as version control (Git), code review, and automated testing concepts.
• bility to troubleshoot issues using logs/metrics and to communicate clearly with teammates and stakeholders about progress, risks, and next steps.
• Commitment to secure development and responsible data handling (e.g., least privilege, secrets management, and following data governance standards)

Key Responsibilities:

• Build and enhance data pipelines to ingest, transform, validate, and publish datasets used for quantitative research and downstream analytics.
• Implement data-quality controls (e.g., schema checks, completeness/accuracy rules, anomaly detection) and contribute to data lineage, documentation, and operational runbooks.
• Contribute to our data platform and supporting services (APIs, shared libraries, workflow orchestration, scheduling), with an emphasis on maintainability, performance, and reliability.
• Write clean, testable code and practice disciplined engineering: unit/integration tests, code reviews, version control, and adherence to Schwab development standards.
• Collaborate with DevOps, production support, and partner technology teams to deliver supportable solutions, including CI/CD, monitoring/alerting, and day-2 operational readiness.
• Participate in Agile ceremonies (standups, grooming, sprint planning, demos, retros) and communicate progress, risks, and dependencies clearly and early.
• Support incident triage and problem management by analyzing logs/metrics, identifying root causes, and driving fixes to reduce recurrence (with mentorship as needed).
• Apply security and compliance best practices (least privilege, secrets handling, secure coding) and follow data governance guidelines when handling sensitive information.
• Leverage modern development tools—including AI-assisted coding tools where appropriate—to accelerate delivery while maintaining high quality, correctness, and proper review practices.