Senior Engineer, Enterprise Data Governance

What you'll do

• Own the roadmap for sensitive information detection and remediation in collaboration with Finance, Legal, and Security teams.
• Integrate ML-based classification models to detect and manage sensitive content across unstructured data at scale.
• Drive production rollout and self-service onboarding for a multi-platform enterprise data access system.
• Design and implement export-control enforcement, audit logging, and RBAC controls across all connected systems.
• Integrate diverse content sources into the AI knowledge platform while ensuring accuracy and authorized access.
• Enforce quality standards for content ingestion regarding freshness, accuracy, and access-control correctness.
• Serve as a technical lead to make architectural decisions and resolve ambiguity across multiple project charters.
• Raise engineering standards through code reviews, design reviews, and technical mentorship of other engineers.

What we're looking for

• Bachelor's or Master's Degree in Computer Science, Computer Engineering, or a related field (or equivalent experience).
• 8+ years of experience building and operating large-scale enterprise platforms with demonstrated growth in technical scope.
• Strong foundation in backend systems, distributed systems, and data engineering for reliability and scale.
• Experience building or integrating data connectors or enterprise SaaS integrations like Confluence, SharePoint, Google Drive, Slack, or Teams.
• Experience training and evaluating ML models for classification tasks in security, content sensitivity, or information governance.
• Strong communication skills to translate complex technical tradeoffs into clear recommendations for non-technical stakeholders.
• Familiarity with access control models, remediation workflows, and audit requirements in enterprise security or compliance contexts.
• Experience with AI/LLM data pipelines, vector stores, RAG architectures, or tools like Databricks and Glean.