Elastic search developer

Elasticsearch Developer

Position:

Experience:

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Role Overview

Elasticsearch Developer

This role requires deep technical proficiency, strong analytical skills, and experience working in high-performance, data-intensive environments.

Key Responsibilities

Elasticsearch & ELK Stack Engineering

• Design, implement, and manage highly scalable and resilient

  Elasticsearch

  and

  ELK (Elasticsearch, Logstash, Kibana)

  stack solutions.
• 
  Architect optimized data structures, indices, mappings, and pipelines to support complex search and analytics use cases.
• Develop and fine-tune

  bulk data ingestion

  and indexing processes for high-volume datasets.
• 
  Perform cluster configuration, monitoring, performance tuning, and troubleshooting.

Elastic Cache & High-Performance Data Solutions

• Implement and optimize caching solutions using

  ElastiCache

  (Redis/Memcached).
• 
  Build and tune high-performance application data flows integrating Elasticsearch and ElastiCache.
• 
  Ensure low-latency processing and retrieval for large-scale applications.

Data Engineering & Query Optimization

• 
  Write complex search queries, aggregations, and filters using Elasticsearch Query DSL.
• 
  Develop high-performance scripts, jobs, and APIs that interact with Elasticsearch and ElastiCache.
• 
  Work with large datasets and design efficient data models, pipelines, and search strategies.
• 
  Optimize queries and implement best practices for speed, accuracy, and scalability.

Reporting & API Development

• 
  Build and maintain reporting solutions using APIs that leverage Elasticsearch and ElastiCache.
• 
  Develop dashboards, analytics visualizations, and operational insights using Kibana or custom reporting frameworks.

Required Skills & Experience

7+ years of overall experience

• Proven experience with

  ELK Stack

  : Elasticsearch, Logstash, Kibana.
• Strong knowledge of

  ElastiCache

  (Redis or Memcached) for caching and performance optimization.
• Experience designing and tuning

  index mappings, analyzers, ingest pipelines

  , and bulk load processes.
• 
  Proficiency with Elasticsearch Query DSL and writing optimized, complex queries.
• Solid understanding of

  distributed systems

  ,

  search algorithms

  , and

  scalability concepts

  .
• 
  Experience building data-driven applications using APIs.
• Strong background in working with

  large datasets

  , performance tuning, and data modeling.

Preferred Qualifications

• 
  Experience with AWS services related to search and caching (e.g., Amazon Elasticsearch Service, OpenSearch, Lambda, S3).
• 
  Familiarity with Python, Java, or Node.js for backend integration scripts.
• 
  Experience with DevOps tools related to monitoring, logging, CI/CD, and infrastructure as code.
• 
  Knowledge of microservices and event-driven architectures.