Data Classification, Standards and Definitions Partner - Job Architecture & Skills

Job Title: Data Classification, Standards and Definitions Partner - Job Architecture & Skills
Job Type: Permanent/Fulltime
Job Location: Hyderabad Hub
About The Job
The Skills, Tasks, and Job Architecture Data Classification Partner is a newly created, strategically critical individual contributor role and has been established in direct response to one of Sanofi's most urgent and high-priority strategic imperatives: the integration of skills and tasks data into the Data Foundation within the upcoming year in support of Sanofi's skills-based organization transformation.
This role is the designer of enterprise data governance frameworks, standards, and data quality rules for the Skills, Tasks, and Job Architecture domains and owns the governance infrastructure that makes the data trustworthy and AI-ready.
Key Responsibilities
Data Governance Framework Design & Ownership
Design the enterprise data governance frameworks, standards, and data quality rules for the Skills, Tasks, and Job Architecture domains ensuring it serves business outcomes
Translate governance decisions and policy updates into usable, consistent, and actionable data assets across the Skills, Tasks, and Job Architecture domains
Document and maintain approved data definitions and data quality rules for Skills, Tasks, and Job Architecture data
Ensure the data catalogue is complete, accurate, and continuously up to date —including definitions, ownership, lineage, sensitivity classification, and data quality rules
Classify data assets including sensitivity classification, ensuring full compliance with governance and regulatory requirements
Manage data sharing agreements for all cross-domain data exchanges involving Skills, Tasks, and Job Architecture data
Ensure Job Architecture data consistency and alignment across global regions and functions
Data Quality Campaign Design & Governance
Design and run the data quality check framework across source systems and the Data Foundation — defining rules, ownership, review cycles, and escalation paths
Derive and drive proactive data quality campaigns across Skills, Tasks, and Job Architecture data domains — identifying patterns of poor data quality, designing targeted remediation campaigns, and coordinating with team members to execute them at scale
Investigate root causes of systemic data issues across Workday — diagnosing structural problems and translating findings into corrective governance actions and campaign-based remediation efforts
Monitor data quality trends over time, using insights to continuously improve data quality rules, checks, and governance standards
Data Foundation Enablement & Technical Governance
Enable Skills, Tasks, and Job Architecture data for the Data Foundation, serving as the key SME to the Data Foundation team within the assigned scope
Ensure data consistency, lineage and traceability from source systems through to the Data Foundation
Own the SkyHive interface on the technical lineage and data catalog side: maintain data lineage documentation for the Workday-to-SkyHive data feed, ensure SkyHive data assets are cataloged in Informatica CDGC, and govern the technical data sharing agreement for the SkyHive integration
Support AI and analytics initiatives through proper data classification and standardization
Ensure data governance frameworks are in place to support current and future AI usage of Skills, Tasks, and Job Architecture data
Build knowledge content on data governance and classification for AI initiatives and employees across the organisation
Workday Configuration Analysis & Root Cause Analysis
Analyse local Workday rules, validations, and configurations that impact global standardisation efforts for Skills, Tasks, and Job Architecture data
Identify where local configurations block the cloning or deployment of global standard configurations
Separate genuine legal and compliance constraints from legacy or preference-based local rules to enable informed global standardisation decisions
Domain Expertise & Stakeholder Engagement
Serve as the key global point of contact for data governance, data classification, and data catalog matters across Skills, Tasks, and Job Architecture data
Partner to drive adoption of global data standards across all regions and functions
Train and support Local Data Champions across regions and business units
Support Data & Insights Team and analysts on relevant data matters to enable trusted reporting and analytics
Collaborate with the Digital Team on data configuration matters, providing expertise on data-related aspects and ensuring alignment between system configurations and data governance standards
About You
Required Qualifications
Bachelor's degree in Data Science, Information Technology, HR Analytics, Business Analytics, or a related field
Strong understanding of Workday architecture, configurations, and data structures
5+ years of experience in data management, HR analytics, or analytical roles
Knowledge of data governance tools and methodologies, data lineage, data cataloging, and metadata management practices
Familiarity with data quality assessment and remediation techniques
Understanding of regulatory compliance requirements (GDPR, data privacy, etc.)
Excellent analytical and problem-solving skills with attention to detail
Strong communication skills with ability to translate technical concepts for business stakeholders
Project management capabilities with experience leading cross-functional initiatives
Preferred Qualifications
Workday certification in HCM, Financial Management, or related modules
Experience with data governance frameworks (DAMA-DMBOK, DCAM, etc.)
Knowledge of AI/ML data requirements and data preparation processes
Experience in pharmaceutical, healthcare, or highly regulated industries
Change management skills and ability to influence without direct authority
Global mindset with understanding of regional compliance and business requirements
Experience with the SkyHive skills intelligence platform
Experience working with Data Foundation / Snowflake environments
Experience with the Cornerstone learning and talent management platform
Strong hands-on experience with Skills, Jobs, Tasks, and Job Architecture data domains
Strong experience with Job Architecture data structures, taxonomies, and governance

Work arrangement
No