Manager, Data Engineering

Your Opportunity

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 Technology Services (STS) enables the future of how clients manage their money by delivering innovative, reliable technology solutions that support investing and financial planning at scale. As a Manager, Data Engineering on the Business Data Delivery team, you will play a critical role in building and advancing enterprise data solutions that power analytics, reporting, and data-driven decision making across the firm.

 

In this role, you will partner closely with business stakeholders, data engineers, architects, product teams, and technology leaders to design and deliver scalable data integration and data warehousing solutions. You will influence technical direction, solve complex data challenges, and help drive strategic outcomes by leveraging modern cloud technologies, advanced data engineering practices, and enterprise-grade governance standards. Success in this role requires balancing technical depth with leadership, bringing together distributed teams, driving continuous improvement, and delivering solutions that create measurable business value.

 

You will have the opportunity to lead large-scale initiatives involving cloud data platforms, enterprise data pipelines, and modernization efforts while mentoring engineers and promoting engineering excellence. Your ability to make sound decisions, navigate ambiguity, and collaborate across diverse teams will directly contribute to the delivery of high-quality, scalable data capabilities that support Schwab's client-centric mission.

What you have

Required Qualifications

 

• 10+ years of experience in Data Engineering, ETL Development, Data Warehousing, or related disciplines.
• 8+ years of experience designing, developing, and implementing enterprise-scale data integration and ETL solutions.
• Define and implement data warehouse, data modeling, ETL, load plans, and performance tuning strategies to ensure solutions meet functional and non-functional requirements. Leverage deep expertise in Data Warehousing, Data Modeling, SQL, and GCP technologies to deliver scalable and reliable platforms.
• Advanced experience with Informatica IDMC/IICS.
• Advanced experience with Google Cloud Platform (GCP), including BigQuery, Google Cloud Storage (GCS), and Dataproc.
• Advanced SQL development and performance optimization experience.
• Experience designing and implementing scalable data warehouse solutions, data models, ETL frameworks, and load strategies.
• Experience supporting batch, near real-time, and real-time data integration architectures.
• Experience with Python and Shell scripting for data engineering and automation initiatives.
• Experience implementing development, testing, Agile, DevOps, and CI/CD best practices.
• Experience using source control and deployment tools such as GitHub, GitLab, Bitbucket, Bamboo, and Control-M.
• Demonstrated ability to lead large-scale or multi-project technology initiatives from design through implementation.
• Experience collaborating with business stakeholders, architects, analysts, and cross-functional technology teams to deliver business-driven solutions.
• Demonstrated ability to analyze complex problems, evaluate alternatives, and drive sound technical decisions.
• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent combination of education and experience.

Preferred Qualifications

• Experience within Financial Services, Wealth Management, Banking, or related regulated industries.
• Experience leading distributed, onshore, offshore, and vendor-supported engineering teams.
• Experience supporting enterprise applications such as Workday and other large-scale business platforms.
• Knowledge of enterprise data governance, data quality, and operational reliability practices.
• Experience mentoring engineers and developing technical talent.
• Strong written and verbal communication skills with the ability to influence technical and business stakeholders.
• Demonstrated ability to drive innovation, process improvement, and modernization initiatives.
• Experience leading strategic planning, prioritization, and technology roadmap discussions.
• Experience creating scalable solutions for analytics, reporting, and data science workloads.
• Proven ability to operate effectively in fast-paced, evolving environments while balancing multiple priorities.

 

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