Manager, Content Data Engineering

This is a fully remote position, open to applicants in Colorado, +5 more states.

📋 Description

• Oversee both offshore and internal teams, which includes responsibilities for hiring, training, performance management, and employee development.

• Take responsibility for the execution and reliability of content ingestion, metadata extraction, entity resolution, canonical models, and data quality processes.

• Create standards, monitoring systems, SQL-based validation processes, escalation paths, and review routines to enhance search and AI capabilities at scale.

• Collaborate with Product and Engineering teams to define the structured data and metadata requirements for customer-facing search, benchmarking, analytics, and AI experiences.

• Clearly convey technical concepts, trade-offs, and data quality considerations to engineering, product, and business stakeholders.

• Implement monitoring, quality metrics, and improvement practices to detect regressions, adapt to changes in source content, and enhance metadata accuracy and completeness.

• Strategize and execute data platform enhancements while balancing the introduction of new capabilities, addressing technical debt, and managing maintenance priorities.

• Foster continuous improvement in data quality, reliability, and operational processes.

⛳️ Requirements

• Proven experience in leading content engineering, data engineering, information engineering, or similar roles focused on converting structured and unstructured content into reliable information products.

• Demonstrated experience in leading and mentoring teams in a managerial role.

• In-depth knowledge of content ingestion, metadata extraction, entity resolution, data modeling, and information quality.

• Experience in automating metadata extraction, normalization, and enrichment processes using suitable rule-based, machine learning, or LLM-based methods.

• Strong understanding of normalized data modeling, canonical entity design, metadata schemas, and provenance.

• High proficiency in relational databases, SQL, and data storage technologies, including conducting investigation, validation, monitoring, and analysis tasks.

• Excellent analytical, root-cause analysis, and problem-solving abilities with an emphasis on customer-facing data quality and reliability.

• Capacity to collaborate effectively with both technical and non-technical stakeholders while managing competing priorities.

🏝️ Benefits

• Initiatives promoting work/life balance

• Well-being initiatives

• Shared parental leave

• Study assistance

• Sabbaticals