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Xebia

Global IT consultancy delivering digital transformation

Senior Technical Product Manager - Search, Metadata & Enrichment

Technical Product ManagementPosted on Nov 14
Full-timeRemote in USANo salary listed

About the Job

Requirements

  • At least 8 years of product management experience, ideally including hands-on platform or data operations experience.
  • Strong requirements documentation, quality assurance, user acceptance testing, and test-plan execution skills.
  • Expertise using Jira and Confluence for backlog management, traceability, and documentation.
  • Working experience with an enterprise search or information retrieval stack such as Elasticsearch, OpenSearch, or Solr, including indexing, relevance tuning, faceted search, and troubleshooting query or ranking issues.
  • Hands-on experience with a metadata management platform, including managing lineage, ownership, glossary terms, and data quality annotations.
  • Ability to operate in complex, multi-system technical landscapes and reason about cross-system and downstream impact.
  • Ability to take ownership of undefined enrichment or metadata problems and drive them to resolution without a fully scoped brief.
  • Understanding of data enrichment concepts, including entity extraction or named entity recognition, classification or tagging, record linkage, and data quality scoring.
  • Experience in pharmaceutical or regulated industry environments, including GxP or 21 CFR Part 11.

Responsibilities

  • Represent the voice of the customer to ensure end delivery provides the desired value.
  • Execute test plans and user acceptance testing ahead of every release against the Data Store and Document Store.
  • Verify that requirements drafted in an approved Product Development Plan appear correctly in the shipped release, owning requirements traceability from the Product Development Plan through Jira stories to release.
  • Flag gaps, regressions, or scope drift before launch and support go/no-go release decisions.
  • Identify systemic patterns in release defects or requirements drift and propose process fixes.
  • Own hands-on enrichment pipeline work, including triaging tagging or classification issues, resolving metadata gaps, and cleaning data quality issues through to completion.
  • Enable maintenance and curation of metadata in the metadata management system, including ownership, descriptions, glossary terms, lineage, and data quality annotations, so assets remain discoverable and trustworthy.
  • Monitor and triage search quality issues, including missing results, poor relevance, indexing gaps, and stale content, in partnership with engineering.
  • Drive ongoing improvement of search relevance and ranking as content and enrichment pipelines evolve, contributing informed opinions on indexing strategy and query or relevance tuning.
  • Spot and escalate systemic metadata and enrichment quality issues across the catalog.
  • Partner with engineering on day-to-day health, uptime, and incident triage for the Data Store and Document Store.
  • Navigate a complex, multi-system data landscape and reason about cross-system impact before changes ship.
  • Understand the underlying architecture, including APIs, data flows, and pipelines, well enough to have technical conversations with engineers and data scientists.
  • Monitor support channels, triage incoming technical requests, and route them appropriately.
  • Serve as a point of contact for researchers and end-users reporting data, search, or enrichment issues.
  • Contribute an informed point of view on trade-offs in roadmap and prioritization discussions for the Data Store and Document Store.
  • Maintain backlog hygiene, documentation, and requirements traceability in Jira and Confluence.
  • Participate in stand-ups, retrospectives, and release reviews.
  • Produce communications announcing functionality to users and supporting their success.
  • Support technical evaluations of other consultants when required, contributing to the assessment of skills and alignment with project needs.

Desired Qualifications

  • Knowledge graph experience, including familiarity with RDF, OWL, SPARQL, property-graph query languages such as Cypher, ontologies or taxonomies, or controlled vocabularies such as MeSH, ChEBI, UniProt, or internal glossaries.
  • Familiarity with GCP services such as BigQuery, Cloud Run, and GCS relevant to the data and search stack.
  • Prior experience managing or contributing to a scientific or technical data catalog at enterprise scale.
  • Background bridging scientific users, including chemists, biologists, or computational scientists, and engineering teams.
  • Track record of spotting and resolving systemic data quality issues rather than only symptomatic fixes.
  • Exposure to applying generative AI or large language model tooling, such as Gemini or Atlassian Intelligence, for documentation generation, requirements automation, or intelligent backlog prioritization.

About the Company

Xebia

Global IT consultancy delivering digital transformation

Xebia is an IT consultancy that helps organizations transform through digital strategy, software delivery, and technology enablement. It offers services such as Digital Strategy, DevOps and SRE, Agile, Data and AI, Cloud, Microsoft Solutions, Low Code, and Xebia Academy, delivered by a global network of 3,100 professionals across 17 offices. The company operates through specialized chapters and partner brands to provide end-to-end digital consulting, offshoring, and nearshoring, focusing on practical, hands-on technology work. Its goal is to enable client transformation by delivering usable technology solutions and building capabilities inside client organizations.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Atlanta, GA
Founded
2001

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