Staff Engineer

🕒 4 dias atrás

🌐 Estados Unidos, Canadá – Remoto

🇺🇸 Estados Unidos – Remoto (EUA) 🇨🇦 Canadá – Remoto

🔔 Pennsylvania – Remoto

🔔 Pennsylvania – Remote

⏰ Tempo Integral

🔴 Especialista

🧑‍💻 Engenheiro Full-stack

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Nagarro

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1996

💼 Consultoria

📣 Marketing

🏥 Saúde

Consulting • Marketing • Healthcare

Nagarro é um líder global em engenharia digital e consultoria de tecnologia. A empresa ajuda os clientes a se tornarem negócios inovadores e digitais, aproveitando a tecnologia para impulsionar avanços nos negócios. Conhecido por sua agilidade empreendedora e mentalidade CARINHOSA, a Nagarro oferece uma ampla gama de serviços, incluindo engenharia digital, soluções empresariais inteligentes e serviços de experiência e design. Com mais de 17. 900 funcionários em 37 países, a Nagarro colabora com líderes do setor para acelerar a digitalização e a inovação orientada pela tecnologia.

Descrição

• Design and govern data architecture for unstructured knowledge assets across the client's Knowledge Management ecosystem • Design logical and physical data models for unstructured and semi-structured content from KM pipelines • Define domain boundaries and ownership for data products • Establish metadata standards and tagging taxonomies for consistent classification across knowledge sources • Assign and enforce security and sensitivity classifications in line with data governance, privacy and legal/risk requirements • Register, document and maintain data products in Databricks Unity Catalog, including schemas, access grants, lineage and catalog-level metadata • Partner with data engineers to align ingestion, transformation and storage patterns with modeled domain structures • Collaborate with Knowledge Products, Research Products and Architecture/Data/Technology stakeholders on downstream consumption needs • Support privacy and legal review processes by ensuring data products are classified and documented • Establish repeatable modeling standards and playbooks for onboarding future data products • Define and adopt a domain model and metadata taxonomy for at least one major KM data product line • Make data products discoverable in Unity Catalog with correct security classifications • Reduce privacy/legal classification review turnaround through consistent metadata and tagging

🎯 Requisitos

• 7+ years of experience in data modeling, information architecture or enterprise data architecture (mandatory skills) • Strong experience designing conceptual, logical and physical data models for enterprise data platforms • Strong understanding of entities, relationships, metadata, master/reference data and data lineage • Experience with taxonomy, ontology, semantic models and controlled vocabularies • Hands-on experience with Databricks, Delta Lake and Unity Catalog or comparable modern data platforms • Ability to translate business concepts and unstructured information into structured, reusable data models • Experience designing knowledge graphs, ontologies and semantic knowledge models • Experience with GenAI/RAG knowledge models and vector/embedding representations • Experience modeling documents, document elements, entities, relationships, evidence and provenance • Knowledge of Neo4j, RDF or property graphs • Experience with Commercial/Customer/CRM domain models, SharePoint content or enterprise knowledge platforms • 5+ years of experience in data modeling, data architecture, or information architecture, with meaningful exposure to unstructured or semi-structured data • Direct experience in or adjacent to Knowledge Management, content management, or enterprise search • Hands-on experience with a modern data catalog; Databricks Unity Catalog strongly preferred • Demonstrated ability to define data domains and data product boundaries in a large, multi-stakeholder organization • Practical knowledge of metadata management, including tagging schemas, taxonomies, controlled vocabularies, or ontology design • Understanding of data security/sensitivity classification frameworks and access control in a lakehouse environment • Experience partnering with data engineering teams on ingestion and pipeline design • Strong written and verbal communication skills • Experience with enterprise knowledge platforms such as Glean, SharePoint or ServiceNow, or AI-powered retrieval systems • Familiarity with Databricks Delta Lake, Delta Sharing or Lakehouse Federation • Prior experience in professional services, consulting, or a similar document/case-intensive knowledge environment • Exposure to Legal/Risk/Privacy review processes for data classification and access approvals • Background in library science, information science, or applied ontology is a plus but not required

🏖️ Benefícios

• 100% remote work • Equal employment opportunities without discrimination • Inclusive work environment • Diverse and dynamic, non-hierarchical work culture