Senior Software Engineer - Confluent

Introduction

At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world.

Your Role And Responsibilities

The Observability Metrics Platform team builds and runs the system that collects, stores and serves metrics for Confluent Cloud. Those metrics power the customer-facing Metrics API, usage and billing signals, internal alerting and dashboards, and integrations that push metrics into customers own observability tools. We operate Apache Druid, the ingestion and pre-processing pipeline, and the query services behind them, across AWS, GCP and Azure, with strict targets for freshness, query latency and availability.

As a Senior Software Engineer, you will design and ship features in this stack, keep it fast and reliable as data volume grows, and work with the product teams across Confluent that depend on it to understand and operate their services. Your work directly improves how Confluent and its customers see the health of their data infrastructure.

What You Will Do

• Design, build and operate high-throughput, low-latency services for metrics ingestion, storage and querying in a multi-tenant, multi-cloud environment
• Own projects end to end: turn ambiguous requirements into clear milestones and deliver production-ready changes with tests, dashboards and alerts
• Improve the reliability and performance of the metrics pipeline and Druid clusters, including ingestion lag, query latency, capacity, upgrades and rollouts
• Troubleshoot complex production issues across microservices, Kubernetes and data stores, take part in on-call, and drive RCAs through to follow-up fixes
• Raise the technical bar through design documents, thoughtful code reviews and mentoring of less experienced engineers
• Partner with product, platform and security teams to onboard new signals, define SLOs and balance reliability, cost and customer impact
• Reduce operational toil by improving runbooks, automation and infrastructure as code
  
  

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• 3 to 5 years of professional software engineering experience building and running backend or data-intensive systems in production
• Strong programming and algorithmic skills in Java
• Solid grounding in distributed systems: partitioning, replication, failure handling and performance tuning
• Experience designing, deploying and operating services on Kubernetes in a public cloud (AWS, Azure or GCP)
• Hands-on production experience: monitoring, debugging, incident response and on-call
• Good engineering habits: automated testing, code review, design documents and clear written communication
• Ability to own work end to end and collaborate effectively across teams
  
  

Preferred Technical And Professional Experience

• Experience with observability concepts and tools: metrics, traces and logs, for example OpenTelemetry, Prometheus, Grafana or Datadog
• Experience with real-time analytics or time-series stores (Apache Druid, Pinot, ClickHouse) or streaming systems such as Apache Kafka or Flink
• Experience tuning ingestion and query performance, or planning capacity, for large datasets
• Experience with Terraform or similar infrastructure-as-code tooling
• Experience with migrations or multi-region rollouts, such as moving workloads from legacy to new architectures