Job Description
Senior Elasticsearch Developer
Chennai
About the Role
We're seeking an experienced Elasticsearch consultant to architect and implement a high-performance analytics dashboard solution that will transform how our organization delivers self-service BI capabilities. This is a critical infrastructure initiative that will sit alongside our existing Oracle data warehouse, enabling sub-second query performance for interactive dashboards and ad-hoc analytics.
What You'll Do
Architecture & Design
Design a scalable Elasticsearch cluster architecture optimized for analytical workloads and dashboard queries
Define data modeling strategies that balance query performance, storage efficiency, and update patterns
Architect the integration layer between our Oracle data warehouse and Elasticsearch, including CDC/ETL pipelines
Establish index design patterns, sharding strategies, and data lifecycle management policies
Implementation & Integration
Build robust data ingestion pipelines from Oracle to Elasticsearch with appropriate transformation logic
Implement search and aggregation queries optimized for dashboard performance
Develop monitoring and observability solutions for cluster health and query performance
Create comprehensive documentation covering architecture decisions, operational procedures, and best practices
Performance & Optimization
Tune cluster configurations, index settings, and query patterns for ultra-fast response times
Implement caching strategies and query optimization techniques
Conduct load testing and capacity planning to ensure production readiness
Establish performance benchmarks and SLAs for dashboard response times
What You Bring
Required Experience
8+ years of hands-on experience with Elasticsearch in production environments, particularly for analytics use cases
Proven track record designing and implementing Elasticsearch solutions that support interactive dashboards and BI tools
Deep understanding of Elasticsearch internals: inverted indices, segment merging, scoring algorithms, and aggregation frameworks
Strong experience with data pipeline design, including ETL/ELT patterns and change data capture
Expertise in performance tuning, capacity planning, and troubleshooting production Elasticsearch clusters
Experience integrating Elasticsearch with traditional data warehouses (Oracle)
Technical Skills
Expert-level knowledge of Elasticsearch Query DSL, aggregations, and search APIs
Strong understanding of distributed systems concepts: sharding, replication, consistency models
Experience with infrastructure as code (Terraform preferred) and cloud platforms (AWS, Azure, or GCP)
Solid SQL skills and understanding of relational data modeling concepts
Familiarity with BI/visualization tools (Tableau, React UI Dashboards or similar)
Highly Valued
Experience with financial services or regulated industry data
Background working with Oracle databases and understanding of Oracle-specific features
Knowledge of real-time analytics architectures and streaming data patterns
Experience with Elasticsearch security features, including RBAC and field-level security
Familiarity with machine learning capabilities in Elasticsearch
Chennai
About the Role
We're seeking an experienced Elasticsearch consultant to architect and implement a high-performance analytics dashboard solution that will transform how our organization delivers self-service BI capabilities. This is a critical infrastructure initiative that will sit alongside our existing Oracle data warehouse, enabling sub-second query performance for interactive dashboards and ad-hoc analytics.
What You'll Do
Architecture & Design
Design a scalable Elasticsearch cluster architecture optimized for analytical workloads and dashboard queries
Define data modeling strategies that balance query performance, storage efficiency, and update patterns
Architect the integration layer between our Oracle data warehouse and Elasticsearch, including CDC/ETL pipelines
Establish index design patterns, sharding strategies, and data lifecycle management policies
Implementation & Integration
Build robust data ingestion pipelines from Oracle to Elasticsearch with appropriate transformation logic
Implement search and aggregation queries optimized for dashboard performance
Develop monitoring and observability solutions for cluster health and query performance
Create comprehensive documentation covering architecture decisions, operational procedures, and best practices
Performance & Optimization
Tune cluster configurations, index settings, and query patterns for ultra-fast response times
Implement caching strategies and query optimization techniques
Conduct load testing and capacity planning to ensure production readiness
Establish performance benchmarks and SLAs for dashboard response times
What You Bring
Required Experience
8+ years of hands-on experience with Elasticsearch in production environments, particularly for analytics use cases
Proven track record designing and implementing Elasticsearch solutions that support interactive dashboards and BI tools
Deep understanding of Elasticsearch internals: inverted indices, segment merging, scoring algorithms, and aggregation frameworks
Strong experience with data pipeline design, including ETL/ELT patterns and change data capture
Expertise in performance tuning, capacity planning, and troubleshooting production Elasticsearch clusters
Experience integrating Elasticsearch with traditional data warehouses (Oracle)
Technical Skills
Expert-level knowledge of Elasticsearch Query DSL, aggregations, and search APIs
Strong understanding of distributed systems concepts: sharding, replication, consistency models
Experience with infrastructure as code (Terraform preferred) and cloud platforms (AWS, Azure, or GCP)
Solid SQL skills and understanding of relational data modeling concepts
Familiarity with BI/visualization tools (Tableau, React UI Dashboards or similar)
Highly Valued
Experience with financial services or regulated industry data
Background working with Oracle databases and understanding of Oracle-specific features
Knowledge of real-time analytics architectures and streaming data patterns
Experience with Elasticsearch security features, including RBAC and field-level security
Familiarity with machine learning capabilities in Elasticsearch
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