Data Engineering

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.

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 Advisor Services, a division of Charles Schwab & Co., Inc. is the leading provider of custody, trading, technology, and practice management to registered investment advisors (RIAs).  Schwab Advisor Services serves over 16,000 independent advisory firms who custody over $5 trillion of assets with Schwab.

This individual will be a part of the Offer Development, Delivery and Analytics department within Advisor Services. Specific to the analytics function, the department delivers data-driven insights and enables accountability through the tracking and reporting of key metrics.

What you will do: Success in this role means delivering reliable, scalable data solutions that enable timely decision-making, while proactively improving data quality, platform performance, and engineering practices.

The Manager, Data Engineering is an individual contributor role. This role supports the creation, maintenance, and operational support of business-unit data assets, data mart solutions, reporting, and analytics that enable business leaders to make decisions and drive continuous process improvement. The role works across business and technical teams to define requirements, metric logic, and data definitions; develop and troubleshoot ETL/ELT logic using SQL and team tooling; complete testing; and provide ongoing maintenance and operational support for code, workflows, and utilities, including job monitoring, issue resolution, and user support.

We’re looking for a hands-on data engineer with strong technical and business acumen who performs well in a structured, fast-paced environment and is passionate about building high-quality, high-performance, and scalable solutions. This role is well suited for someone who is motivated to learn and understand corporate systems, reinforce engineering best practices, streamline existing processes, and contribute to a future-state data platform that improves client-centricity, speed to market, scale, and efficiency. The ideal candidate is comfortable creating structure, working through ambiguity, and adapting to change.

Responsibilities include: Data Engineering & Architecture

Build and maintain data mart solutions that support reporting and analytics use cases.

Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data. Develop and troubleshoot ETL/ELT logic using SQL and team tooling.

Design and build dimensional data models, including facts and dimensions, determine appropriate table grain, and implement slowly changing dimensions where historical tracking is required.

Define and implement practical data retention and history strategies that preserve analytical value without overloading downstream reporting tools.

Data Quality, Reliability & Operations

Implement and maintain data quality controls, reconciliation checks, testing, and monitoring to ensure data accuracy, consistency, and reliability.

Support production reliability through job monitoring, issue resolution, root-cause analysis, operational support, and documentation.

Create and maintain production support and deployment artifacts.

Collaboration & Delivery

Collaborate with business stakeholders and technical teams to translate business needs into scalable technical solutions, including metric logic, and data definitions.

Work closely with development partners, product owners, and team members to design features, decompose stories, and prioritize delivery.

Share technical knowledge and support team success through collaboration, documentation,