Data Engineering Lead

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 is seeking a results-driven, strategic data engineering leader to help advance our enterprise data platform as we modernize and scale capabilities across the firm. In this role, you will lead the design, development, and continuous improvement of high-performance, scalable data solutions that power critical business functions including risk, compliance, audit, and corporate systems. You will operate at the intersection of technology and business, translating complex requirements into actionable data solutions while driving measurable outcomes such as improved system stability, faster time to market, and stronger data quality and governance.

As a hands-on technical leader, you will guide and mentor a team of engineers, fostering a culture of accountability, collaboration, and continuous improvement. You will partner closely with product owners, developers, and cross-functional stakeholders to prioritize work, decompose complex initiatives, and ensure aligned, high-quality delivery. Success in this role requires the ability to navigate ambiguity, make informed decisions, and proactively identify risks and dependencies to keep projects on track.

You will play a key role in strengthening operational intelligence through the firm's data exchange platform, driving innovation across data pipelines, enabling automation, and supporting enterprise-wide data accessibility. This is an opportunity to shape the future state of Schwab's data ecosystem-building resilient, efficient, and scalable solutions that enable better business decisions and enhance the client experience.

What you have

Required Qualifications

• 12+ years of data engineering experience delivering scalable data pipelines, platforms, and solutions
• 7+ years of experience leading strategic projects and driving delivery in a matrixed organization
• 5+ years of experience within financial services or a regulated industry
• Strong expertise in data architecture, data modeling, data quality frameworks, and ETL development, with a focus on building reliable, high-performing systems
• Advanced proficiency in SQL and Python, with experience leveraging modern data platforms and cloud technologies (e.g., Google Cloud Platform services such as BigQuery, Dataflow, Cloud Storage, Composer, Pub/Sub)
• Experience with enterprise data integration tools such as Informatica and SQL Server Integration Services (SSIS)
• Demonstrated ability to translate business needs into technical data solutions and guide teams through data analysis and mapping processes
• Proven leadership experience building, developing, and mentoring high-performing engineering teams across varied skill levels
• Strong understanding of data warehouse concepts, including star schema, slowly changing dimensions, and fact/dimension modeling
• Knowledge of data lifecycle management, metadata management, and data governance best practices
• Experience implementing data security controls and access management to protect sensitive information
• Strong problem-solving skills with the ability to assess risks, make data-driven decisions, and drive resolution
• Excellent communication skills, with the ability to effectively influence and collaborate with both technical and non-technical stakeholders
• Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience)

Preferred Qualifications

• Experience working with enterprise systems such as Workday, BMC Remedy Helix, Jira, or Rally
• Familiarity with event-driven and streaming architectures, including tools such as Kafka
• Experience with data visualization and reporting tools, including report design and delivery of insights
• Proficiency with development and DevOps tools such as GitHub, Bamboo, or Liquibase
• Experience in cloud-native data engineering practices, with a preference for Google Cloud Platform
• Demonstrated ability to manage multiple priorities in a fast-paced, geographically dispersed environment while maintaining strong organizational discipline

In addition to the salary range, this role is also eligible for bonus or incentive opportunities.