Senior Search Engineer - OpenSearch

Search is how our users get their work done. In OMS+, finding the right material, customer, order, or document in seconds can bethe difference between a smooth order and a lost one.Often across catalogs with millions of items and decades of enterprise history behind them.

We are looking for a Senior Search Engineer with OpenSearch expertiseto join the team. The role is split between product and delivery: you will help design and build the search capabilities that ship with the platform, then work with customer data and customer teams to make them perform in theirenvironments.

The focus throughout is search design and build: index and schema design, indexing pipelines fed from SAP source systems, relevance engineering, and the search APIs our TypeScript product stack consumes. What we need from this role is design judgement.Things like how indexes should be shaped, how queries should be written, and how to prove a relevance change

improved results.

Key Responsibilities

• Help design index mappings, analyzers, and sharding strategies suited to large, high-cardinality enterprise catalogs.

• Help build and maintainindexing pipelines that keep search

  in syncwith SAP source systems, including full reindex and incremental update paths.

• Design and tune queries: query DSL, scoring and boosting, synonyms, stemming, fuzzy and typo tolerance, faceting, and aggregations.

• Contribute to relevance measurement.

• Support delivery engagements: profile customer catalogs, tune index and query design, and work with implementation and solution engineering on customer-specific relevance requirements.

• Diagnose and fix search performanceproblems: expensive queries, mappingand analyzer design, sharding choices, and data modeling.

• Implement vector and hybrid search alongside lexical search where semantic matching measurablyimproves results.

• Understand and specify platform needs: cluster sizing and configuration, index lifecycle policies, snapshotand upgrade requirements.

• Help build clean, well-documented search APIs for the TypeScript product stack, and define the search health and quality signals the platform should surface.

• Work with product management on roadmap search priorities, and withsolution engineering on multi-tenant considerations.

• Document search architecture and relevance decisions so the rest of engineering can reason aboutthem.

• Review search-related work from teammates and help raise the team's standards for query design and relevance rigor.

Required Qualifications

• Deep, hands-on OpenSearch or Elasticsearch expertise, ideally with productionsearch you designed and built yourself.

• Command of the query DSL, mappings, analyzers, and aggregations, and a working mental model of the relevance levers each one gives you.

• Proven relevance engineering: you have measurably improved search quality and can explain how you proved it.

• A solid grasp of how index and cluster design choices drive performance:sharding, mapping design, query cost, Lucene fundamentals, etc.

• Strong debugging ability for search problems: slow or expensive queries, mapping and analyzer mistakes, and results that are wrong in ways users notice before dashboards do.

• Experience building high-throughput ingestion and indexing pipelines against systems of record.

• Proficiencyin TypeScript/JavaScript and/or Python for building services, pipelines, and tooling.

• Comfort working directly with customers and delivery teams.

• Comfort working alongside a separate platform or IT team: specifying requirements, handing off cleanly, and collaborating on diagnosis rather than reaching for root access.

• Clear communication and a habit of documenting decisions, particularly around relevancetrade-offs.

• Bachelor's degree in Computer Scienceor a related technical field, or equivalent practical experience.

Preferred Qualifications

• Vector and semantic search experience: embeddings, the OpenSearch k-NN plugin, hybrid ranking, or learning-to-rank.

• Familiarity with OpenSearch Dashboards, Data Prepper, Logstash, or Kafka-based ingestion.

• Experience with SAP or ERP material master and catalog data, including part numbers, cross-references, and unit-of-measure complexity.

• Query understanding:entity extraction, intent classification, spell correction, autocomplete.

• Multi-tenant search architecture and tenant data isolation.

• Experience in a customer-facing implementation, delivery, or professional services capacity.

• Working knowledge of containers and Kubernetes.

• Contributions to OpenSearch, Lucene, or other open sourcesearch projects.

Ready to apply? Please upload your resume in English.

DataXstream Inc., is an equal-opportunityworkplace and an affirmative-action employer. We are always committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Discrimination is not welcome on the basis of any other status protected by the laws or regulations in the locations where we work.