Drive the multi-quarter technical roadmap and design large-scale OpenSearch clusters capable of handling petabytes of data with low-latency indexing and query performance.
Deeply integrate OpenSearch with CDP components (e.g., Apache Iceberg, SDX, and Ozone) to provide a unified search experience across the data lakehouse.
Lead efforts to optimize JVM settings, shard allocation strategies, and query DSL to ensure maximum throughput and stability.
Oversee the development of Kubernetes Operators and Helm charts for automated deployment, scaling, and self-healing of search services.
Define and champion best practices for security (RBAC, TLS), observability, and enterprise-grade reliability.
Mentor senior and junior engineers on complex technical designs and foster a culture of continuous improvement across the organization.
Act as a primary liaison and influencer within the upstream OpenSearch community, aligning their roadmap with product strategy.
Requirements
Bachelor’s degree in Computer Science or equivalent, and 6+ years of experience; OR Master’s degree and 4-6 years of experience; OR PhD and 2-4 years of experience
6+ years of experience working with OpenSearch or Elasticsearch in production environments at scale.
Distributed Systems: Deep understanding of consensus algorithms, CAP theorem, replication, and sharding.
Programming: Mastery of Java (for core development) and proficiency in Go or Python for automation and tooling.
Infrastructure: Extensive experience with Kubernetes (K8s) and container orchestration.
Cloud Platforms: Hands-on experience deploying search workloads on AWS (EKS/AOSS), Azure (AKS), or Google Cloud (GKE).