Senior Confluent Kafka Platform Admin

Charles Schwab Inc.•Austin, TX

7d•$164,000 - $190,000•Onsite

About The Position

Schwab’s Event Streaming team in the Enterprise Middleware organization is seeking a senior Kafka platform engineer to lead the evolution of its enterprise event-streaming platform. The role focuses on enterprise-scale event streaming, Confluent Cloud adoption, platform efficiency, and AI-enabled SDLC transformation. The selected candidate will work on site in the specified location(s). The position provides technical leadership across Confluent Platform and Confluent Cloud, advances cloud modernization and platform resiliency, and builds automation to improve scalability, security, reliability, performance, stability, and developer productivity. The role combines Kafka administration expertise with Java development, cloud and Kubernetes experience, and the ability to apply AI-assisted engineering to accelerate delivery and improve operational efficiency for secure, business-critical solutions.

Requirements

Bachelor’s degree in computer science, engineering, or a related field.
10+ years of hands-on software engineering experience with proven technical leadership.
5+ years of expertise in large-scale distributed systems and mission-critical infrastructure.
Strong hands-on experience with GitHub Copilot and other AI-assisted development tools, including advanced prompt engineering and workflow integration.
Proven ability to use AI-assisted development, such as Copilot and code generation, and build AI-driven agents or workflows to improve productivity and engineering efficiency.
Deep expertise in Confluent Kafka, including capacity planning, administration, internals, and performance tuning.
Strong experience with Kafka clusters, replication, disaster recovery, and data pipelines.
Hands-on experience with Kubernetes, Confluent Operator, and cloud-native modernization using GCP.
Strong development background on Linux/Unix platforms.
Experience with data modeling and streaming technologies, including Avro, Protobuf, and JSON Schema.
Hands-on expertise in Python, Ansible, and CI/CD pipelines, including Jenkins and DevOps tooling, to improve operational efficiency and reduce manual effort.
Solid foundation in security engineering, including encryption, TLS, and certificate and key management.
Strong focus on observability, reliability, automation, production readiness, and proactive risk mitigation.
Experience leading architecture and execution across cross-functional, large-scale programs.
Strong understanding of networking, load balancing, operating-system fundamentals, and performance optimization.
Experience in regulated environments; financial services experience is preferred.
Strong collaboration skills across engineering, architecture, infrastructure, and business teams.
Experience working with globally distributed or offshore teams.
Strong Agile delivery experience, including Scrum, Kanban, or Scaled Agile.
Leadership skills including strategic thinking, decision-making, mentoring or coaching, and driving engineering excellence.
Excellent communication, influencing, and stakeholder management skills, including the ability to align diverse teams.
High ownership, prioritization, multitasking, and leadership skills in high-pressure production situations.
Strong problem-solving skills and a proactive, innovation-driven approach.
Self-driven, adaptable, and customer-focused, with strong relationship-management and team-building capabilities.

Nice To Haves

Experience applying AI-Driven Development Lifecycle (AI-DLC) practices to modernize SDLC pipelines through intelligent automation and improve development, testing, and release efficiency.
Demonstrated contributions to architecture standards, reusable frameworks, or open-source initiatives in distributed systems or event-driven platforms.
Deep expertise in Kafka platform administration and development, including large-scale event-streaming systems and enterprise platform modernization.
Confluent Kafka, Confluent Cloud, or major cloud platform certifications (GCP, AWS, or Azure).

Responsibilities

Design and build AI agents, custom skills, or equivalent frameworks to automate engineering and operational workflows at scale.
Use AI-powered tools, including Copilot and AI agents, to accelerate development, automate testing, improve code quality, and enable intelligent SDLC workflows aligned with the AI-DLC vision.
Design agentic workflows and multi-agent orchestration patterns for complex distributed systems, integration, and operational challenges.
Serve as the senior technical authority for Confluent Platform and Confluent Cloud, providing architecture, design, and implementation guidance for enterprise integration challenges.
Lead solution architecture across cross-functional initiatives, aligning solutions with cloud modernization, resiliency, security, and AI-driven engineering priorities.
Analyze complex production issues, identify root causes, implement sustainable remediation strategies, and fully document the work.
Design and build automation frameworks and self-service tools to streamline Kafka operations, reduce manual effort, and improve developer productivity and platform scalability.
Lead migrations of on-premises Kafka workloads to Confluent Cloud using cluster linking, schema portability, and hybrid streaming patterns while avoiding business disruption.
Coordinate Kafka, infrastructure, security, and application teams to remove dependencies, mitigate risks, and deliver milestones on time.
Contribute to enterprise architecture forums and define and enforce event-streaming, integration, and platform-standardization best practices.
Establish best practices for testing, reliability, observability, and operational readiness to support high availability and scalable performance.
Identify systemic and architectural risks and lead mitigation efforts to prevent client impact and maintain platform stability.
Implement enterprise-grade security controls, including mTLS, RBAC, and encryption, and continuously remediate vulnerabilities to meet regulatory and audit requirements.
Interpret technical requirements and build or enhance Kafka configurations, message flows, and integration solutions for business-critical applications.
Partner with distributed teams, including offshore engineering, to maintain consistent standards, efficient delivery, and 24x7 operational support across time zones.