Skills & Experience
- 8+ years of experience in platform engineering, SRE, or distributed systems-focused roles.
- Demonstrated subject matter expertise in operating at least one of MongoDB, Kafka, or ElasticSearch at high scale, including deep day-2 operational knowledge.
- Significant experience designing and operating large-scale, Kubernetes environments and associated ecosystem tooling (e.g. Helm, Kustomize, ArgoCD etc.). Experience managing stateful workloads on Kubernetes is a significant plus.
- Proven experience defining architectural standards and influencing technical direction across teams.
- Robust programming skills (Python, Java, or similar), with experience building internal platform APIs and automation tooling a significant plus.
- Extensive experience with Infrastructure as Code (e.g. Terraform) and cloud-native deployment models.
- Hands-on experience operating enterprise-scale workloads in AWS.
- Experience designing and evolving observability platforms (e.g. Prometheus/Grafana, ELK) to support multi-cluster environments.
- Solid understanding of security principles and experience embedding security best practices into production environments and code promotion systems.
- Excellent communication skills with the ability to influence diverse technical and non technical stakeholders
Core Responsibilities
- Define and evolve the architectural vision and operating standards for large-scale distributed data platforms.
- Lead the design and evolution of highly available, scalable clusters supporting core data technologies including MongoDB, Elasticsearch, and Apache Kafka.
- Solve complex, ambiguous distributed systems problems, balancing trade-offs across scalability, resilience, performance, security, and cost.
- Influence engineering teams to adopt platform standards, automation practices, and self service capabilities.
- Partner with engineering and product leadership to align platform capabilities with strategic business objectives.
- Establish re