Senior Kafka Platform Engineer
A top Asset Management firm is looking for a seasoned Kafka Engineer to design, operate, and scale their event streaming platform in a high-performance environment. This role is architecture-oriented, with a strong emphasis on automation, Kubernetes, and reliability engineering. You'll own the Kafka core-brokers, storage, security, observability-and build automation that powers it, using Infrastructure-as-Code, Operators, Helm, and CI/CD for safe, repeatable deployments.
You'll run Kafka on Kubernetes and/or cloud-managed offerings, ensure reliability and performance, and partner with application teams to define best practices.
What You'll Do
- Architect, deploy, and operate production-grade Kafka clusters (self-managed and/or Confluent/MSK), including upgrades, capacity planning, multi-AZ/region DR, and performance tuning.
- Operate Kafka on Kubernetes using Operators, Helm, and GitOps; build IaC-driven automation with guardrails for zero-downtime provisioning.
- Implement and manage Kafka Connect, Schema Registry, and MirrorMaker 2/Cluster Linking; standardize connectors (e.g., Debezium) and enable self-service patterns.
- Drive reliability: define SLOs/error budgets, on-call rotations, incident response, postmortems, runbooks, and automated remediation.
- Implement observability: metrics, logs, traces, lag monitoring, and capacity dashboards (Prometheus/Grafana, Burrow, Cruise Control, OpenTelemetry).
- Secure the platform: TLS/mTLS, SASL (OAuth/SCRAM), RBAC/ACLs, secrets management, network policies, audit, and compliance automation.
- Guide event-streaming best practices: topic design, partitioning, retention, idempotency, ordering, schema evolution, DLQs, EOS semantics.
- Collaborate with app, data, and SRE teams; provide enablement, documentation, and internal tooling for a great developer experience.
- Lead and mentor engineers; contribute to roadmap, standards, and platform strategy.
Required Qualifications
- Deep hands-on experience operating Kafka at scale in Big Tech, trading, or asset management environments.
- Strong Kubernetes expertise running stateful systems.
- Automation-first mindset: Infrastructure as Code (Terraform), Helm, Operators, GitOps (Argo CD/Flux), and CI/CD (GitHub Actions/Jenkins).
- Proficiency in Python, Go, or Java, plus Bash and solid Linux fundamentals (networking, filesystems, JVM tuning basics).
- Observability and reliability engineering for Kafka: Prometheus/Grafana, logging, alerting, lag monitoring, capacity/throughput modeling, performance tuning.
- Security for data in motion: TLS/mTLS, SASL/OAuth, ACL/RBAC, secrets management (Vault), and audit/compliance practices.
- Experience with Kafka ecosystem components: Kafka Connect, Schema Registry, MirrorMaker 2/Cluster Linking; familiarity with Cruise Control.
- Cloud experience (AWS/Azure/GCP) with networking, IAM, and managed offerings (Confluent Cloud or AWS MSK).
- Proven track record designing runbooks, leading incidents/postmortems, and driving platform roadmaps.
Nice to Have
- Data processing frameworks (Kafka Streams, Flink, Spark Structured Streaming) and EOS semantics.
- Experience with Strimzi or Confluent for Kubernetes in production.
- Knowledge of CDC patterns and tools (Debezium) and database connectors at scale.
- Multi-region architectures, cluster linking strategies, and disaster recovery drills.
FAQs
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