Charles Schwab is re-architecting and rebuilding its Wealth & Asset Management Engineering core central data platform and needs a technical engineering leader to lead the effort and drive significant step-change in time to market, building more stable integrated solutions, and enabling project success via cross-functional coordination and ownership
Requirements
- Ability to read and understand code written in languages used by the team (e.g., Python, Java, SQL) for effective communication and collaboration
- Knowledge of the Snowflake ecosystem, including internal and external stages, Snowpark, Streamlit, and data architectures built for Snowflake
- Proficient in data engineering concepts including data modeling, data warehousing, data orchestration (e.g., Airflow), monitoring/observability, and data governance
- Knowledge and experience working with data pipelines, data warehousing, data storage solutions (on-premises and cloud-based), and familiarity with data technologies (e.g., Python, SQL, Java, Informatica, C)
- Knowledge and experience working with webservices and/or API specifications and ability to work with API Engineers in translating requirements into secure, scalable, resilient, and performant solutions
- Subject matter expertise with the Financial Asset Management Industry domains along with experience with external vendor products Including Eagle Data Management, Rimes, BlackRock Aladdin, State Street, Morningstar, and Bloomberg
- Proven experience working with a Data Management team and familiar with concepts like security master, product master, and pricing master data
Responsibilities
- Lead a high-performing team of data engineers and leads supporting data pipelines, reporting, and exchange across key business domains
- Provide strategic, technical and project leadership to data pipeline development
- Drive end-to-end ownership of the development lifecycle including intake, estimation, design, build, test, and support
- Collaborate with cross-functional stakeholders (Product Owners, Data Architects, QA, and Infrastructure teams) to define priorities and resource allocation
- Implement best practices in SDLC, Agile/Scrum methodologies, and DevOps automation in a data engineering context
- Govern platform health, technical debt, and capacity planning while ensuring adherence to compliance, audit, and information security guidelines
- Hands-on development and mentoring for all members of the team to ensure team and project success
Other
- A university degree from a well-respected academic institution; advanced degrees in Information management, Computer Science, Business Administration and/or other professional certifications
- Minimum 12+ years of experience in data engineering with a proven track record of leading and managing teams of 5-15 people
- Minimum 12+ years of experience working in financial services with a strong understanding of investment management data
- Excellent communication and interpersonal skills, with the ability to translate technical concepts for both technical and non-technical audiences
- CFA certification
