Technical Lead, Data Platform Infastructure

Governance Data Engineer (Data Catalog / Metadata / Controls)

Location: Boston, MA (Onsite 4 days/week)

About Our Client

Our client is building foundational AI, Data, and Platform capabilities that enable global scale and business transformation. Their platform engineering organization evolves technology into robust, reusable platform solutions that improve agility, strengthen controls, and deliver measurable business impact.

The Role

Our client is hiring a Governance Data Engineer (Lead level) to join their core AI/Data/Platform engineering team in Boston. This is a pivotal, hands-on technical leadership role focused on building enterprise-grade data management and governance capabilities-including a universal data catalog, metadata management, semantic definitions, lineage, entitlements, and SOX-aligned controls.

You'll define how the organization structures, documents, and governs data so it is discoverable, trustworthy, auditable, and AI-ready-supporting analytics, reporting, and agentic AI use cases in a highly controlled environment.

Work model: Onsite in Boston 4 days per week.

What You'll Do

• Lead the design and implementation of enterprise data management capabilities, with a focus on:
  • Universal data catalog
  • Metadata management
  • Standardized data definitions across platforms and domains
• Partner with business, technology, risk, and control stakeholders to define and operationalize semantic data models that improve consistency, usability, and interoperability for analytics, reporting, and AI-enabled workflows
• Build and mature SOX-aligned data governance frameworks including data ownership, lineage, controls, policy adherence, and documentation standards to support regulatory, audit, and operational requirements
• Simplify and modernize data entitlement models, enabling scalable policy-based access management that balances security, compliance, and usability across users, applications, and AI agents
• Establish operating models, standards, and governance processes that increase data discoverability, trust, and reuse while reducing fragmentation and manual effort
• Translate strategic data priorities into an executable roadmap, influence cross-functional delivery teams, and ensure implementations are scalable, practical, and aligned to enterprise architecture
• Improve "AI-readiness" of the data foundation by strengthening metadata quality, access patterns, semantic structure, and governance controls required for trusted agentic AI adoption
• Serve as a senior contributor and thought partner-shaping best practices, managing stakeholder expectations, and driving measurable progress against data transformation goals
• Mentor and elevate engineers across multiple teams

What Our Client Is Looking For

• Bachelor's or master's degree in Computer Science, Engineering, or related field
• 8 years of experience in data engineering, data architecture, data management, or related disciplines, including leadership on enterprise-scale initiatives in complex, highly controlled environments
• Deep expertise in:
  • Data cataloging and metadata management
  • Data lineage and governance frameworks
  • Auditability / controls / regulatory compliance-oriented implementations
• Strong stakeholder management and communication skills-able to align engineering, product, analytics, risk/controls, and business partners and drive execution across cross-functional teams

Why This Role

• High-leverage, enterprise-impact work: you'll define the governance foundation that enables trustworthy analytics, reporting, and AI adoption
• A role with real scope: catalog metadata semantic definitions entitlements SOX-aligned governance
• Visible leadership: influence multiple teams and set standards that scale across a complex organization