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. Schwab Technology Services enables the future of how clients manage their money by providing innovative and reliable technology products and services as part of our ongoing commitment to democratize access to investing and financial planning. 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).
Schwab Asset Management Technology supports the research and asset management platforms that help clients plan for their financial futures. Within this organization, the Investment Research Technology team builds and supports applications used by Schwab professionals and clients to make informed investment decisions.
As a
Software Engineer (hands-on) for Research Technology, you'll lead through impact-contributing code, guiding technical direction, and mentoring others as we modernize key research capabilities across on-premises and cloud environments. You'll partner closely with product, architecture, and research stakeholders in an Agile and DevOps model to deliver secure, scalable solutions that improve the experience for the people who rely on Schwab's research platforms every day.
Key Responsibilities- Build and deliver full-stack software capabilities for investment research initiatives, contributing hands-on to design, development, testing, and support.
- Translate business needs into clear technical approaches by partnering with product owners, researchers, architects, and engineering peers.
- Design and implement cloud-ready, event-driven services and integration patterns that improve scalability, reliability, and reuse across the broader platform.
- Drive engineering excellence through clean code practices, automated testing, observability, and secure-by-design delivery.
- Strengthen the team's delivery model by improving CI/CD workflows and DevOps practices to increase quality and speed to production.
- Diagnose and resolve complex production and integration issues using deep application and environment knowledge, while improving long-term resiliency.
- Mentor and support engineers through coaching, feedback, and inclusive collaboration-helping the team grow capabilities and confidence.
- Lead with ownership and transparency by communicating priorities, tradeoffs, and progress to both technical and business partners.
- Contribute to modernization efforts that improve user experience and align with evolving architecture standards.
- Incorporate approved Generative AI capabilities to enhance developer productivity and code quality while following enterprise governance, security, and compliance expectations.
What you have- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent practical experience.
- 7+ years of experience developing production-grade applications using Java (Spring Boot) and Python.
- Demonstrated ability to build cloud-ready, event-driven microservices and APIs at scale using common messaging patterns (e.g., Kafka, RabbitMQ) and RESTful services.
- Proven experience designing and building hybrid on-premises and cloud integrations.
- Strong working knowledge of SQL (e.g., PostgreSQL) and NoSQL technologies (e.g., MongoDB, DynamoDB, Bigtable) and when to apply each.
- Ability to work with financial datasets and partner effectively on data engineering workflows and analytics use cases.
- Experience building data visualizations or dashboards using Python-based tooling (e.g., Plotly Dash or similar).
- Hands-on experience using CI/CD and container-based delivery practices (e.g., GitHub CI/CD, Docker, Kubernetes, Bamboo/Jenkins).
- Working knowledge of secure coding and code quality practices using common analysis tools (e.g., SonarQube, CodeQL, Veracode).
- Demonstrated skill in designing maintainable solutions using appropriate data structures, algorithms, and modern design principles.
Preferred Qualifications- Experience modernizing data platforms or research technology in a regulated industry (financial services is a plus).
- Familiarity with rules engines (e.g., Drools) and data lake patterns for large-scale time series datasets.
- Experience collaborating with quantitative partners to enable or operationalize models (Python or R).
- Demonstrated ability to balance near-term delivery with longer-term architecture evolution and platform scalability.
- Strong prioritization and communication skills, including comfort explaining complex technical concepts to dive.
In addition to the salary range, this role is also eligible for bonus or incentive opportunities.
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