Sr. Manager Full Stack Software Engineer at Charles Schwab | JobProMax | JobProMax
Sr. Manager Full Stack Software Engineer
Charles Schwab
Southlake, Texas
Full-Time
Competitive
RemoteManager
Job Description
Pay range: USD $170,000.00 - $180,000.00 / Year
Your opportunity
Do you want to be part of an enterprise data solutions organization managing over 4+ petabytes of data and powering the next-generation analytics and operational data platforms for a leading financial firm with over $10 trillion in assets under management?
At Schwab, the Operational Data Exchange (ODX) organization owns the strategy, architecture, implementation, delivery, and support of enterprise operational data platforms. These platforms are mission-critical to the Contact Center's ongoing modernization, supporting large-scale application transformations (e.g., movement from Genesys to NICE), increased adoption of AI-driven capabilities, and customer experience optimization.
We are seeking a Sr. Manager in a Technical Delivery Lead capacity to provide hands-on technical leadership across the Contact Center Data Exchange portfolio. This is a critical position and is responsible for ensuring that Contact Center data platform modernization keeps pace with application transformation and AI initiatives. The ideal candidate brings recent hands-on engineering experience, strong architectural judgment, and the ability to communicate complex technical topics clearly to senior leadership.
What you'll do:
Own end-to-end technical delivery for Contact Center operational data platforms, ensuring reliability, scalability, and alignment with evolving business priorities.
Provide technical leadership for the modernization of Contact Center data architecture, supporting application migrations, AI-driven capabilities, and real-time operational data use cases.
Lead the Oracle DB migration from on-prem to GCP, driving cloud-native design, resilience, performance optimization, and cost efficiency.
Design and oversee scalable batch and streaming data pipelines using Java, Spring, Kafka-based technologies, and GCP native services (Cloud Run, GKE, Cloud Functions, Pub/Sub, Cloud SQL, Cloud Storage).
Establish and enforce engineering best practices for coding standards, CI/CD, data quality, reliability, security, and observability.
Maintain hands-on involvement in solution design and complex problem-solving while providing technical direction to engineers across onshore and offshore teams.
Partner closely with Contact Center business leaders, platform teams, and upstream application owners to define data contracts, integration patterns, and delivery roadmaps.
Act as a technical liaison to senior leadership, clearly communicating risks, tradeoffs, modernization progress, and platform health.
Proactively identify and mitigate technical debt, delivery risks, and scalability constraints that could impact AI enablement or customer experience outcomes.
Support production operations by driving root-cause analysis, improving platform stability, and reducing incident recurrence through architectural improvements.
Lead, coach, and develop engineering managers and senior engineers, fostering a culture of accountability, inclusion, and continuous improvement.
Own talent strategy for the Contact Center Data Exchange domain, including hiring, onboarding, performance management, career development, and succession planning.
Set clear expectations and goals for teams, aligning individual development plans with organizational outcomes and delivery commitments.
Build sustainable delivery capacity by strengthening leadership bench, improving execution predictability, and promoting strong team ownership across the portfolio.
What you have
Required Qualifications
15+ years of recent, hands-on software engineering experience, with a strong focus on data engineering, APIs, and distributed systems.
5+ years of technical leadership experience, owning delivery for complex, business-critical platforms.
5+ years of people leadership experience, leading multiple cross-functional engineering teams.
Demonstrated experience in building scalable data ingestion frameworks to acquire and integrate data from diverse source systems in real-time, near real-time, and batch modes into operational data stores and enterprise data warehouses for downstream consumption.
Strong understanding of data modeling and storage strategies optimized for both operational and analytical use cases, including designing data structures that support reporting, low-latency access, and high-performance analytics.
Hands-on experience leveraging AI-assisted development tools (e.g., Copilot or similar) to accelerate engineering productivity, automate code generation and testing, and drive measurable improvements in developer efficiency and delivery timelines.
Deep expertise with Java, Spring (Boot/Batch), REST APIs, Microservices, and SQL.
Strong public cloud experience (3+ years), with preference for GCP and cloud-native architecture patterns.
Hands-on experience with streaming technologies such as Kafka, Pub/Sub, Kinesis, or RabbitMQ.
Proven experience leading large-scale data platform migrations or modernization initiatives.
Strong CI/CD experience using tools such as GitHub, Jenkins, Bamboo, Bitbucket, and automated testing frameworks.
Demonstrated ability to communicate effectively with senior leadership, including presenting technical strategies, risks, and outcomes to non-technical audiences.
Recent hands-on experience is required-this role is expected to actively engage in design, troubleshooting, and critical technical decisions.
Demonstrated success building and scaling high-performing engineering organizations with strong retention and engagement.
Preferred Qualifications
Contact Center domain experience, particularly within a data organization, supporting platforms such as Genesys, NICE, or similar ecosystems.
Experience supporting AI-enabled operational use cases, real-time analytics, or intelligent routing systems.
Experience with Operational Data Stores / Exchanges, enterprise data integration, and high-availability data platforms.
Working knowledge of data warehousing concepts, Informatica IDMC / Power Center, or similar ETL technologies.
Prior experience serving as a technical lead for distributed, cross-geography teams.
What's in it for you
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.
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
Responsibilities
Own end-to-end technical delivery for Contact Center operational data platforms, ensuring reliability, scalability, and alignment with evolving business priorities.
Provide technical leadership for the modernization of Contact Center data architecture, supporting application migrations, AI-driven capabilities, and real-time operational data use cases.
Lead the Oracle DB migration from on-prem to GCP, driving cloud-native design, resilience, performance optimization, and cost efficiency.
Design and oversee scalable batch and streaming data pipelines using Java, Spring, Kafka-based technologies, and GCP native services (Cloud Run, GKE, Cloud Functions, Pub/Sub, Cloud SQL, Cloud Storage).
Establish and enforce engineering best practices for coding standards, CI/CD, data quality, reliability, security, and observability.
Maintain hands-on involvement in solution design and complex problem-solving while providing technical direction to engineers across onshore and offshore teams.
Partner closely with Contact Center business leaders, platform teams, and upstream application owners to define data contracts, integration patterns, and delivery roadmaps.
Act as a technical liaison to senior leadership, clearly communicating risks, tradeoffs, modernization progress, and platform health.
Proactively identify and mitigate technical debt, delivery risks, and scalability constraints that could impact AI enablement or customer experience outcomes.
Support production operations by driving root-cause analysis, improving platform stability, and reducing incident recurrence through architectural improvements.
Lead, coach, and develop engineering managers and senior engineers, fostering a culture of accountability, inclusion, and continuous improvement.
Own talent strategy for the Contact Center Data Exchange domain, including hiring, onboarding, performance management, career development, and succession planning.
Set clear expectations and goals for teams, aligning individual development plans with organizational outcomes and delivery commitments.
Build sustainable delivery capacity by strengthening leadership bench, improving execution predictability, and promoting strong team ownership across the portfolio.
15+ years of recent, hands-on software engineering experience, with a strong focus on data engineering, APIs, and distributed systems.
5+ years of technical leadership experience, owning delivery for complex, business-critical platforms.
5+ years of people leadership experience, leading multiple cross-functional engineering teams.
Demonstrated experience in building scalable data ingestion frameworks to acquire and integrate data from diverse source systems in real-time, near real-time, and batch modes into operational data stores and enterprise data warehouses for downstream consumption.
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Job Details
Job Type
Full-Time
Workplace Type
Remote
Experience Level
Manager
Salary
Competitive
Categories
Software Engineering
Strong understanding of data modeling and storage strategies optimized for both operational and analytical use cases, including designing data structures that support reporting, low-latency access, and high-performance analytics.
Hands-on experience leveraging AI-assisted development tools (e.g., Copilot or similar) to accelerate engineering productivity, automate code generation and testing, and drive measurable improvements in developer efficiency and delivery timelines.
