We are building and scaling a distributed data platform that handles high-volume OpenRTB/ad data ingestion and retention. The engineer will work closely with our System Architect to design, optimize, and maintain Elasticsearch clusters as a core part of our data infrastructure.

MANDATORY SKILLS (Must Have) :

- Minimum 2 years of hands-on Elasticsearch experience

- Strong understanding of Elasticsearch index design, mappings, and settings

- Experience with index lifecycle management (ILM) policies

- Proficiency in writing complex queries (aggregations, filters, nested queries)

- Experience with hot-warm-cold data tier architecture

- Knowledge of Elasticsearch cluster management (nodes, shards, replicas)

- Hands-on experience with Kibana for monitoring and visualization

- Familiarity with data ingestion pipelines (Logstash / Kafka / custom pipelines)

GOOD TO HAVE SKILLS :

- Experience with OpenRTB / AdTech data

- Knowledge of Apache Kafka for event-driven architectures

- Familiarity with Python or Java for scripting/integration with Elasticsearch

- Experience with Bloom filters or other optimization techniques for large-scale data

- Exposure to Parquet / object storage (S3/GCS) for data archival

- Understanding of microservices and distributed system design

KEY RESPONSIBILITIES :

- Design and maintain Elasticsearch indices optimized for high-volume data

- Implement and manage ILM policies for automated data retention

- Optimize query performance and cluster health

- Collaborate with the architecture team on scalable data storage solutions

- Work on data retention strategies for specific device/entity-level data beyond standard retention windows

- Monitor and troubleshoot cluster performance, shard allocation, and storage