Manager, Data Engineering

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field.
• 10+ years of experience in Data Engineering, Data Warehousing, ETL Development, or related disciplines.
• Experience leading large-scale data engineering initiatives, technical teams, or complex enterprise programs.
• 5+ years of experience designing and implementing enterprise data integration solutions using Informatica IDMC/IICS or similar ETL technologies.
• Experience with Google Cloud Platform (GCP), including services such as BigQuery, Google Cloud Storage (GCS), and Dataproc.
• 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 developing scalable data ingestion, transformation, and integration solutions supporting batch, near real-time, and real-time processing patterns.
• Demonstrated expertise in Data Warehousing, Data Modeling, ETL Architecture, and SQL Development.
• Strong programming and scripting experience utilizing Python, Shell Scripting, and related automation technologies.
• Experience designing and optimizing high-performance data platforms through performance tuning, workload optimization, and scalable architecture practices.
• Experience partnering with business stakeholders, business analysts, architects, and cross-functional technology teams to deliver business-focused data solutions.
• Proven experience developing technical specifications, testing strategies, operational documentation, and governance controls for enterprise data platforms.
• Working knowledge of Agile delivery methodologies, DevOps practices, CI/CD pipelines, and modern software engineering principles.
• Experience utilizing source control and deployment tools such as GitHub, GitLab, Bitbucket, Bamboo, Control-M, or comparable technologies.
• Strong analytical, problem-solving, and decision-making skills with the ability to lead complex technical initiatives from concept through delivery.
• Excellent verbal and written communication skills with the ability to influence technical and non-technical stakeholders., * Experience within financial services, banking, brokerage, wealth management, or other highly regulated industries.
• Experience supporting enterprise applications such as Workday, CAT, O2, SPO, or similar business-critical platforms.
• Experience leading distributed, offshore, and vendor-supported engineering teams.
• Demonstrated ability to drive technology modernization, process improvement, and data platform transformation initiatives.
• Experience fostering engineering best practices, mentoring teams, and building high-performing technical organizations.
• Strong background in strategic planning, prioritization, and execution across multiple concurrent initiatives.
• Experience influencing architectural standards, governance frameworks, and enterprise data strategies.
• Proven ability to navigate ambiguity, adapt to changing business priorities, and drive successful outcomes in complex environments.

We offer a competitive benefits package that takes care of the whole you - both today and in the future:

• 401(k) with company match and Employee stock purchase plan
• Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions
• Paid parental leave and family building benefits
• Tuition reimbursement
• Health, dental, and vision insurance

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, secure, and reliable technology solutions that support investing, financial planning, and wealth management at scale. As a Manager, Data Engineering on the Business Data Delivery team, you will play a critical role in shaping enterprise data solutions that power analytics, reporting, and data science initiatives across the organization.

In this role, you will lead the design, development, and delivery of complex data integration and data platform solutions that enable business stakeholders to make informed decisions and create better client outcomes. Partnering closely with business leaders, product teams, data modelers, architects, and fellow engineers, you will transform data into actionable insights through scalable and resilient data pipelines, data warehouse solutions, and cloud-based platforms. Your expertise will influence strategic technology decisions, drive engineering excellence, and support critical business capabilities across a variety of financial services applications.

You will have the opportunity to work with modern cloud and data technologies including Google Cloud Platform (GCP), BigQuery, Informatica IDMC/IICS, Dataproc, Control-M, SQL, Python, and enterprise DevOps tools. Beyond technical leadership, you will mentor engineers, guide delivery teams, and foster a culture focused on innovation, continuous improvement, collaboration, and operational excellence. This is an exciting opportunity for a leader who is passionate about solving complex data challenges, driving business impact, and helping shape the future of Schwab’s enterprise data ecosystem., At Schwab, you’re empowered to shape your future. We champion your growth through meaningful work, continuous learning, and a culture of trust and collaboration-so you can build the skills to make a lasting impact. Our Hybrid Work and Flexibility approach balances our ongoing commitment to workplace flexibility, serving our clients, and our strong belief in the value of being together in person on a regular basis.