Senior Elasticsearch Engineer

Job not on LinkedIn

🕒 July 21

🌏 Anywhere in the World

⏰ Full Time

🟠 Senior

đŸ‘·đŸ»â€â™€ïž Engineer

đŸ‘» Ghost score 10%

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Logo of Chess.com

Chess.com

501 - 1000 employees

Founded 2007

🎼 Gaming

📚 Education

đŸ“± Media

💰 Private Equity Round on 2022-01

Gaming ‱ Education ‱ Media

Chess. com is the leading online platform for playing and learning chess, offering a wide range of features such as live gameplay with other players, customizable training bots, chess puzzles, and comprehensive lessons. The platform is highly regarded for enhancing players' pattern recognition and overall chess skills. Chess. com also provides coverage of major chess events like the FIDE World Championship. With a focus on creating a supportive and engaging community for chess players of all levels, Chess. com is a go-to resource for anyone interested in improving their chess game or enjoying competitive play.

📋 Description

‱ Own the full lifecycle of our search and analytics data platform: capacity planning, cluster architecture, performance tuning, incident response, migration strategy, and operational excellence. ‱ Be the single point of deep expertise across all Elasticsearch and OpenSearch clusters at Chess.com. ‱ Hands-on with cluster internals, write ILM/ISM policies, push infrastructure changes through GitOps, and make real-time decisions about replica allocation when a cluster goes red. ‱ On-call ownership for Elasticsearch-related incidents: cluster health degradation, node loss, disk pressure, shard imbalance, and write rejection cascades. ‱ Real-time cluster triage and cross-team coordination during production incidents. ‱ Post-mortem authoring and systemic reliability improvements. ‱ Snapshot and disaster recovery management across clusters. ‱ Advise engineering teams on index design, mapping strategy, retention policies, and query optimization. ‱ Manage Kibana and OpenSearch Dashboards access and configuration for internal consumers. ‱ Define and maintain workload priority tiers across clusters.

🎯 Requirements

‱ 7+ years operating Elasticsearch at scale (multi-TB clusters, dozens of nodes, high write throughput) ‱ Deep understanding of Elasticsearch internals: segment merging, translog, shard allocation, and cluster state management ‱ Production experience with ECK (Elastic Cloud on Kubernetes) or equivalent operator-based deployments ‱ Proficiency with Kubernetes operations for stateful workloads (StatefulSets, persistent storage, resource management) ‱ Hands-on Linux systems administration with a focus on storage and I/O performance ‱ Experience managing both Elasticsearch and OpenSearch in production, including an informed opinion on their respective trade-offs ‱ Incident command experience: ability to diagnose and mitigate cluster emergencies under pressure while communicating clearly to stakeholders ‱ Git-based infrastructure management (GitOps): Helm charts, ArgoCD/Flux, infrastructure-as-code for cluster configuration ‱ Fluency with the Elastic stack APIs: cluster administration, index templates, data streams, ILM policies, snapshot/restore.

đŸ–ïž Benefits

‱ Full autonomy. ‱ Real scale. ‱ Bare metal. ‱ Strategic impact. ‱ Small team, big trust.

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