Software Engineering Associate Advisor - HIH - Evernorth

Requirements

• Required Experience & Education:
• 5 - 8 years of relevant Data Engineering Experience.
• Elasticsearch administration and performance tuning.
• Search relevancy algorithms and semantic search.
• Data backup and disaster recovery in Elastic.
• Python/Java for Elastic API integrations.
• Familiarity with knowledge graph and metadata enrichment.
• Required Skills:
• Elasticsearch, Python/Java for Elastic API integrations, Pyspark, Cloud Experience (AWS/Azure)
• Preferred Skills, Experience & Education:
• graph and metadata enrichment
• About Evernorth Health Services

Benefits

Additional Information

Software Engineering Lead Analyst Evernorth, a leading Health Services company, is looking for exceptional engineers/developers in our Data and Analytics organization. In this role, you will actively participate with your development team on initiatives that support Evernorth's strategic goals as well as subject matter experts to understand business logic you will be engineering. As a software engineer, you will help develop an integrated architectural strategy to support next-generation capabilities on an enterprise-wide scale. You will work in an agile environment, delivering user-oriented products. The ideal candidate will work in a team environment that demands technical excellence, whose members are expected to hold each other accountable for the overall success of the end product. Focus for this team is on the delivery of innovative solutions to complex problems, but also with a mind to drive simplicity in refining and supporting of the solution by others Roles & Responsibilities Responsible for designing, implementing, and optimizing enterprise search solutions and managing Elasticsearch clusters to ensure high availability, scalability, and relevance. Architect and maintain self-hosted Elasticsearch clusters, including node configuration, replication, and sharding strategies. Implement backup and recovery processes for Elastic indices. Develop and optimize semantic search capabilities using machine learning models (e.g., BERT-based ELSER). Enhance search relevancy through role-based indexing and boosting strategies. Collaborate with cross-functional teams to integrate Elastic with knowledge management tools and improve user experience. Monitor cluster performance and apply best practices for scalability and observability.

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