About this role: Wells Fargo is seeking a deeply technical Principal Engineer with elite-level expertise in both IBM MQ and Apache Kafka. This is a hands-on-keyboard role for a subject matter expert who will be the ultimate technical authority for our enterprise messaging and data streaming backbone. You will be responsible for architecting, building, securing, and optimizing our most critical data-in-motion platforms to support high-volume, low-latency financial applications. This is a role for a master engineer who solves the most complex distributed systems challenges. In this role, you will: Architecture & Engineering Architect, build, and optimize enterprise-grade IBM MQ and Apache Kafka infrastructure from the ground up. Design and implement resilient, high-availability (HA) and disaster recovery (DR) topologies, including MQ Multi-Instance Queue Managers/Clusters and Kafka cluster replication (e.g., MirrorMaker2). Engineer solutions for diverse messaging patterns: request/reply, pub/sub, transactional, and event streaming. Define and enforce enterprise standards for MQ queue/channel definitions, Kafka topic naming conventions, partitioning strategies, and data schemas (using Avro/Protobuf and Schema Registry). Serve as the technical design authority for all projects integrating with MQ or Kafka. Implementation & Administration Perform expert-level installation, configuration, and tuning of IBM MQ (Queue Managers, Channels, Listeners) and Kafka (Brokers, Zookeeper/KRaft, Connect). Implement advanced security controls: TLS/SSL for both platforms, Channel Authentication (CHLAUTH) and OAM in MQ, and SASL/SCRAM with ACLs in Kafka. Develop and maintain a robust automation framework (using Ansible, Python, Terraform) for provisioning, configuration management, and operational tasks for both MQ and Kafka. Manage and optimize the Kafka Connect ecosystem, deploying and monitoring connectors for data integration. Performance & Troubleshooting Lead performance tuning efforts to maximize throughput and minimize latency for both MQ and Kafka, focusing on buffer tuning, batching, compression, and log management. Conduct deep-dive root cause analysis (RCA) for production incidents, analyzing FDC files and error logs in MQ, and broker/consumer logs and metrics in Kafka. Utilize advanced debugging tools (e.g., tcpdump, Wireshark, JVM profilers) to diagnose complex network, application, and platform issues. Proactively monitor platform health, consumer lag, message throughput, and system resource utilization using tools like Prometheus, Grafana, and enterprise monitoring suites. Developer & Application Support Act as a senior consultant to application development teams on best practices for using MQI, JMS, and Kafka Producer/Consumer APIs. Troubleshoot critical integration issues, including poison messages, stuck consumers, message ordering conflicts, and idempotent producer problems. Champion the adoption of modern practices like event-driven architecture and stream processing (using Kafka Streams or ksqlDB).