Database Development Engineer

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.

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.

The Workplace Services Engineering - Stock Plan Technology organization leads the development and maintenance of Schwab's Workplace Services platforms to server our clients equity compensation and trade monitoring needs. Our team is seeking a Senior Performance Engineer, who embraces being a technical influencer and has a real passion for helping teams to build performant, stable, and scalable applications using state-of-the-art technologies. Our mission is to build robust solutions that achieve measurable value, which empower our clients. In WSE - SPT, we work hard every day to improve the experience for our clients, using cutting-edge technology and creative solutions to solve hard problems.

What you have

Key Responsibilities
Support ongoing Oracle and SQL Server development initiatives across multiple Schwab SPT platforms. Build and maintain CI/CD pipelines for database changes using Liquibase integration. Develop automated processes to replace manual refresh workflows. Establish and maintain trunk-based development model for database version control with GitHub integration.

Ideal Candidate Profile
Required Qualifications
Hands on experience gained through 4-5+ years of software development with Oracle and SQL server databases

1year+ Schwab technology domain experience gained as a current or recent contractor or employee
Financial and Investment services domain experience with Stock Plan Services.
Experience with database release management tools (Liquibase strongly preferred)
Strong experience with continuous integration/continuous deployment frameworks
Git version control and repository management (GitHub preferred)
Expert level of experience with Python for automation scripting
Generative AI tools (GitHub Copilot) for code generation and optimization
Executes strategies to restore services promptly and address disruptions
Prioritizes compliance, security, and scalability of data systems
Validates requirements and constraints to support effective development and operations
Monitors and addresses security policy violations using best practices
Resolves software design challenges using predictive and adaptive methods
Applies best practices to build, test, and validate software components while resolving issues
Consolidates software changes into secure, stable releases using best practices
Ensures systems align with cloud architectures using modern design methodologies
Preferred Qualifications
What experience and skills are DESIRED, but are not REQUIRED to perform this role today?

Technical nice-to-haves
Cloud platform experience (PCF, AWS, or Google Cloud)
PHP development
Bash shell scripting
Database DevOps toolchain experience
Ensures stakeholders has the necessary information for informed decisions
Identifies opportunities for process improvements and implements creative solutions
Influences team quality and effectiveness with decisions
Applies specialized expertise to support initiatives that optimize performance
Produces work that meets or exceeds quality expectations
Writes concise, well-structured, and engaging business documents

Job Sub-Family Specific Competencies
Architecture Management - Leading the design, implementation, and ongoing support of architectural initiatives from inception to operational maintenance, with a focus on driving initiatives across teams and enterprises
Application Maintenance and Support - Delivering effective management and technical services to address technical issues and minimize disruption to application users
Change Coordination - Coordinating regulated modifications to products, services, or systems while managing associated risks
Data Engineering Fundamentals - Strategically managing and operationalizing data pipelines and storage systems for data mining, analytics, and machine learning, prioritizing compliance, security, and scalability
Data Modeling - Creating, managing, and communicating data requirements and assets through models and diagrams, supporting data operations and governance
Data Management - Strategizing, optimizing, and governing data assets through comprehensive management practices