Data Quality and Metadata Lead

Job Summary

We are seeking a hands-on Senior Manager, Data Quality and Metadata Lead to join our IT Data and AI Platform organization and operationalize a core pillar of Otsuka's Information Governance Program. In this role, you will define and deliver the frameworks, standards, tools, and enablement services that make enterprise data trusted, well-described, and discoverable—for both structured and unstructured content. This role is anchored by three strategic pillars: (1) advancing data quality maturity by defining guidance, frameworks, and training that empower data domain teams to measure, monitor, and improve the quality of their data; (2) establishing metadata and lineage standards that make data assets self-describing, traceable, and connected across the enterprise; and (3) operationalizing platforms such as the enterprise data catalogue and data quality tools so that governance is embedded in the flow of work. At Otsuka, we defy limitation, so that others can too. We have an unwavering belief in doing more. In transcending expectations. In going above and beyond—under any circumstances—for patients, families, providers, and for each other. It's this deep-rooted dedication that drives us to uncover answers to complex, underserved medical needs, so that patients can push past the limitations of their disease and achieve more than they thought was possible each and every day. We believe that the bigger the challenge, the bigger the opportunity. We are doing everything in our power to live up to our mission of creating new products for better health worldwide in two important therapeutic categories: neuroscience and nephrology.

Job Description

The Senior Manager, Data Quality and Metadata Lead will be a key member of the Information Governance team, responsible for establishing and evolving Otsuka's enterprise data quality and metadata management practices. The Senior Manager will partner with Data Stewards, Data Owners, Data Product Owners, and the Enterprise Data Catalogue Platform Owner to translate governance strategy into practical guidance, actionable playbooks, and adopted tools.

Data Quality Framework & Standards

• Define and maintain the enterprise Data Quality Framework, including dimensions (accuracy, completeness, consistency, timeliness, validity, uniqueness), scoring models, thresholds, and remediation practices.
• Establish standards, guardrails, and reusable patterns for data profiling, rule definition, monitoring, and issue management across data domains.
• Publish playbooks, templates, and reference implementations that data domain teams can adopt to accelerate their data quality journey.
• Continuously evolve the framework to reflect emerging best practices, regulatory requirements, and lessons learned from domain implementations.

Data Quality Enablement & Support

• Provide hands-on guidance, coaching, and training to Data Stewards, Data Owners, and Data Product Owners on data quality practices, tools, and metrics.
• Support data domain teams in defining data quality rules, building dashboards, and interpreting results—especially during early adoption.
• Establish a Data Quality Community of Practice to share knowledge, patterns, and lessons learned across domains.
• Partner with domain teams to prioritize and resolve high-impact data quality issues, driving measurable improvement over time.

Metadata & Lineage Management

• Define enterprise standards for business, technical, and operational metadata covering both structured (databases, data warehouses, files) and unstructured (documents, media, content) data.
• Establish guidance for capturing and maintaining data lineage end-to-end—from source systems through pipelines, transformations, analytics, and AI consumption layers.
• Define metadata enrichment practices that support discovery, semantic understanding, and AI grounding (in partnership with the Information Architect).
• Ensure metadata practices support regulatory traceability (e.g., GxP, 21 CFR Part 11, GDPR) and audit readiness.

Platform Operationalization

• Partner with the Enterprise Data Catalogue Platform Owner to operationalize the catalogue (Atlan) as the source of truth for metadata, lineage, and data assets.
• Collaborate with data quality tool owners (e.g., Ataccama DQM) to configure, extend, and adopt the platform in support of domain use cases.
• Define integration patterns between the catalogue, data quality tools, MDM platforms, data pipelines, and analytics platforms to automate metadata capture and quality monitoring.
• Contribute to platform roadmaps and requirements to ensure they meet the evolving needs of the Information Governance program.

Reporting, Metrics & Continuous Improvement

• Define and publish enterprise data q