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# Manager Content Data Engineering

- **Company:** LexisNexis
- **Location:** Rochester, NY, United States
- **Salary:** $115,400.0 - $192,300.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Information Engineering, Data Infrastructure, Relational Databases, Machine Learning, Metadata, SQL Databases, Data Storage Technologies, Large Language Models, Technical Debt, Entity Resolution
- **Published:** October 22, 2026
- **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=3030613149-2

## About the Role

* 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.

## Description

You will lead a team responsible for transforming raw legal and regulatory documents into trusted, structured information that powers Intelligize.

Your team will be responsible for our processes to ingest content, extract and normalize metadata from both structured and unstructured documents, maintain canonical representations of key business entities such as companies, and ensure that hundreds of metadata enrichment processes continue to produce accurate, reliable results as source formats evolve. A strong understanding of SQL and relational data structures will be important for guiding how data is modeled, queried, validated, and improved over time.

You will establish the quality standards, monitoring, and governance needed to ensure that the metadata our products rely on remains trustworthy over time. This includes partnering closely with Product and Engineering teams to make sure the data foundation supports customer-facing search and AI experiences.

Responsibilities

 * 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.