Manager, Content Data Engineering

🕒 il y a 7 jours

🏄 California, Illinois, +4 états de plus – Distant

🏄 California – Remote 🌽 Illinois – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🏈 Ohio – Remote 🦀 Maryland – Remote

💵 $115 400 - $230 700 / an

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🚰 Ingénieur Data

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LexisNexis

Site WebLinkedInTous les Emplois

10 000+ employés

Fondée en 1970

⚖️ Juridique

💼 Conseil

🏥 Santé

💰 Corporate Round en 2021-06

Legal • Consulting • Healthcare

LexisNexis est un fournisseur de solutions professionnelles adaptées aux cabinets d'avocats, aux entreprises, aux agences gouvernementales et aux institutions académiques. Il propose des solutions juridiques, des actualités et des analyses commerciales. LexisNexis offre également des solutions de gestion des risques pour les entreprises et les agences gouvernementales, avec un accent sur l'analyse de données pour la conformité, l'acquisition de clients, la détection de fraude, les résultats de santé, les solutions d'identité, les enquêtes, la gestion des créances, la prise de décision en matière de risques et l'optimisation des flux de travail. En tant que partie du groupe RELX, LexisNexis s'engage à améliorer l'expérience numérique grâce aux données et à l'analyse.

Description

• Lead offshore and internal teams, including hiring, training, performance management, and employee development. • Own execution and reliability for content ingestion, metadata extraction, entity resolution, canonical models, and data quality processes. • Establish standards, monitoring, SQL-based validation, escalation paths, and review routines to support search and AI capabilities at scale. • Partner with Product and Engineering to define structured data and metadata needs for customer-facing search, benchmarking, analytics, and AI experiences. • Communicate technical concepts, tradeoffs, and data quality considerations clearly to engineering, product, and business stakeholders. • Establish monitoring, quality metrics, and improvement practices to identify regressions, adapt to source-content changes, and improve metadata accuracy and completeness. • Plan and deliver data platform enhancements while balancing new capabilities, technical debt, and maintenance priorities. • Drive continuous improvement in data quality, reliability, and operational processes.

🎯 Exigences

• Experience leading content engineering, data engineering, information engineering, or similar functions focused on transforming structured and unstructured content into trusted information products. • Experience leading and developing teams in a management capacity. • Advanced understanding of content ingestion, metadata extraction, entity resolution, data modeling, and information quality. • Experience automating metadata extraction, normalization, and enrichment pipelines using appropriate rule-based, machine learning, or LLM-based approaches. • Strong understanding of normalized data modeling, canonical entity design, metadata schemas, and provenance. • Strong proficiency with relational databases, SQL, and data storage technologies, including investigation, validation, monitoring, and analysis activities. • Strong analytical, root-cause analysis, and problem-solving skills with a focus on customer-facing data quality and reliability. • Ability to collaborate effectively with technical and non-technical stakeholders and manage competing priorities.

🏖️ Avantages

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Remote work options • Study assistance • Sabbaticals