Senior Elasticsearch Expert

About the Role

We are looking for a highly skilled Elasticsearch Expert who can architect, optimize, and evolve our entire search ecosystem. This person will own how search works across millions of products, ensure high-performance indexing and querying, design relevance algorithms, and make sure we utilize Elasticsearch to its maximum capabilities.

You will work closely with Engineering, Data, DevOps and Product teams to ensure our search infrastructure is scalable, resilient, cost-efficient, and delivers the best shopping experience.

Key Responsibilities
1️⃣ Search Architecture Ownership
Design, build, and optimize Elasticsearch clusters for high availability, low latency, and large-scale indexing.
Define index mappings, templates, analyzers, normalizers, tokenizers and custom pipelines suitable for multilingual, e-commerce data.
Architect multi-index strategies (aliases, versioned indices, reindexing flows, rollover, hot-warm tiers).
Implement proper sharding, replication, and routing strategies.

2️⃣ Search Relevance & Ranking
Build relevance ranking systems: boosting, scoring, weighted factors, script scoring.
Implement personalization-aware scoring (behavioral signals, trending, popularity).
Enhance catalogue search for precision, recall, typo handling, and semantic relevance.
Design category-level dynamic ranking and scoring logic.

3️⃣ Advanced Query Engineering
Build dynamic filtering systems (sizes, colors, categories, brands, attributes).
Create complex real-time aggregations for availability, pricing, and insights.
Implement vector search for embeddings (OpenAI or AWS-based semantic search).
Optimize keyword search, fuzzy matching, synonyms, stemming rules, stop-words.

4️⃣ Performance & Scalability
Optimize indexing throughput and speed for millions of documents.
Solve cluster bottlenecks: heap usage, GC tuning, threadpools, cache layers.
Manage ILM (Index Lifecycle Management) for hot/warm/cold architecture.
Design highly available clusters with fault tolerance.

5️⃣ Observability & Maintenance
Implement rich monitoring dashboards (Grafana, Kibana, CloudWatch).
Setup alerts for cluster health, indexing failures, slow queries, JVM pressure.
Perform periodic audits to ensure the cluster remains efficient and stable.

6️⃣ Data Pipeline & Integration
Work with backend teams to design efficient indexing pipelines (queue-based or batch).
Ensure clean, structured, normalized data models for indexing.
Build fallback strategies for partial failures and safe reindexing rollout.

7️⃣ Cost Optimization & Best Practices
Continuously monitor cluster costs and implement optimization:
Hot vs Warm storage
Shard count reduction
Compression techniques
Scaling policies
Recommend cluster upgrades or migration improvements.

Skills & Experience Needed
Must-Have Technical Skills
Strong expertise in:
Mapping design
Custom analyzers
Aggregations
Relevance tuning
Cluster scaling & performance optimization
Index lifecycle management (ILM)

Deep understanding of:
Inverted indices
Doc_values
Fielddata
HNSW vector search
Query DSL & complex scoring logic

Hands-on experience with:
ECS / Kubernetes deployments
AWS managed Elasticsearch / OpenSearch
Node.js or Python-based indexing pipelines
Queues (Kafka/SQS) for ingest

Bonus Skills
Experience building search for e-commerce platforms.
Experience with semantic search, embeddings, LLM integrations.
Experience with A/B testing of ranking algorithms.
Strong data-modelling experience for multi-attribute product catalogs.

Familiarity with log search, fraud signals search, personalization engines.