Data Lead

Overview

Position Description

We are hiring a Data Lead to support a large-scale enterprise transformation program delivering a modern Knowledge Management (KM) solution. In this role, you will lead data-related activities that enable content migration, metadata quality, integration, and the enablement of advanced analytics and AI-enabled capabilities. You will work across business, information management, and technical teams to ensure that data is well understood, appropriately structured, and fit for use across the KM platform, including AI-enabled features that rely on accurate and consistent data.

This role requires deep, practical experience working with enterprise data across structured and unstructured sources, and the ability to translate data requirements into clear direction for migration, integration, and platform teams in a complex, regulated environment.

Data Leadership & Coordination

• Lead data-focused activities supporting the KM solution, including data assessment, profiling, and alignment to target-state information and analytics needs.
• Act as a central point of coordination for data-related considerations across migration, information architecture, and platform work streams.
• Ensure data dependencies, assumptions, and constraints are clearly identified and communicated.

Data Understanding & Analysis

• Analyze existing data sources, structures, and quality issues across legacy systems and repositories.
• Support identification of critical data elements required for knowledge management, reporting, and AI-enabled features.
• Work with business stakeholders and subject matter experts to clarify data meaning, usage, and fitness for purpose.

Data Quality & Readiness

• Define data quality expectations and validation approaches appropriate to the program scope.
• Support data profiling, cleansing, and remediation planning in collaboration with migration and technical teams.
• Identify data quality risks that may impact search, analytics, or AI-assisted functionality.

Metadata, Integration & Information Alignment

• Collaborate closely with Information Architecture and KM teams to align data structures with metadata models, taxonomies, and classification schemes.
• Support mapping between source data and target information structures.
• Ensure data considerations are reflected in integration and platform design decisions.

Support to Migration & AI-Enabled Capabilities

• Provide data leadership input to content and data migration planning and validation activities.
• Support preparation and validation of data used to enable effective search, analytics, and AI-assisted features within the KM solution.
• Review data-related deliverables to ensure alignment with agreed requirements and standards.

Governance & Documentation

• Contribute to data-related standards, documentation, and decision records.
• Support data governance and stewardship practices defined for the program.
• Provide clear data-related inputs to program governance and readiness discussions.

Required

• 10+ years of relevant experience working with enterprise data in roles such as data analysis, data management, data architecture, data engineering, or information management.
• Strong understanding of data structures, data quality, metadata, and data integration concepts.
• Experience supporting data migration initiatives or large-scale platform transitions.
• Working knowledge of how data supports analytics and AI-enabled solutions, including data preparation and fitness-for-use considerations.
• Ability to work across business and technical teams to translate data needs into actionable guidance.
• Experience working in complex, regulated, or public-sector environments.
• Strong analytical, documentation, and communication skills.

Preferred

• Experience supporting Knowledge Management or Enterprise Content Management platforms.
• Exposure to master data management, reference data, or enterprise metadata initiatives.
• Familiarity with cloud-based data platforms and integration patterns.
• Experience supporting AI-enabled or data-driven features from a data readiness or quality perspective.
• Experience working within Agile or hybrid delivery models.