Manager, R&D Data Steward

BeiGene

12d•$123,200 - $163,200•Onsite

About The Position

The Manager, R&D Data Stewardship independently leads stewardship activities for assigned R&D data domains and data products. The role ensures data is well-defined, discoverable, appropriately governed, quality-assessed, and fit for intended use while coordinating with business and technical stakeholders. This individual contributor role applies strong hands-on expertise in metadata and catalog curation, data profiling, data quality, Informatica Data Marketplace, data analysis, automation, and AI-assisted stewardship. The role also coaches other stewards, resolves complex issues, and contributes to stewardship standards and capability improvement.

Requirements

Bachelor’s degree in Life Sciences, Data Management, Information Systems, Computer Science, or a related field, or equivalent relevant experience.
Demonstrated ability to independently deliver data stewardship, metadata and cataloging, data product, profiling, and data-quality activities in a complex environment.
Strong practical knowledge of R&D data domains and the ability to translate business context into governed metadata and quality controls.
Demonstrated analytical and technical capability using SQL and modern data platforms; automation experience is preferred.
Working knowledge of GxP, privacy, data integrity, and regulated data-management practices.
Strong stakeholder management, problem-solving, coaching, and communication skills.

Nice To Haves

automation experience is preferred

Responsibilities

Interpret complex R&D business processes and data flows independently and translate them into governed metadata, business context, and quality controls.
Determine authoritative sources for assigned domains and resolve conflicting interpretations with Data Owners and SMEs.
Act as the stewardship point of contact for assigned R&D domains.
Lead implementation of R&D stewardship standards, workflows, governance metadata, CDE practices, and FAIR data principles for assigned scope.
Independently resolve complex stewardship issues and coordinate decisions with Data Owners, SMEs, Privacy, Quality, Data Engineering, Data Modeling, and other stakeholders.
Contribute to stewardship metrics, prioritization, standards, and continuous improvement of operating practices.
Own curation and quality review of business terms, definitions, aliases, taxonomy, CDEs, classifications, ownership, permitted use, and business-friendly descriptions.
Drive catalog completeness and consistency in Informatica CDGC and apply working knowledge of ontology and semantic concepts to improve business context.
Interpret data models and lineage independently, and coordinate with owning teams when structural or downstream impacts require resolution.
Lead stewardship readiness, certification, publication, lifecycle review, and recertification of assigned data products in Informatica Data Marketplace.
Ensure data products have complete metadata, ownership, business context, quality information, fitness-for-use information, and clear consumer descriptions.
Partner with Data Owners and consumers to address data product usability, trust, and governance gaps.
Independently perform and review complex profiling, including patterns, keys, anomalies, referential checks, and cross-table relationship discovery.
Translate R&D business logic into data-quality rules, thresholds, severity levels, and monitoring expectations with appropriate SMEs.
Lead investigation, disposition, root-cause analysis, and remediation coordination for significant data-quality issues, and coach others through complex cases.
Use SQL, Databricks, Python, and PySpark to analyze data, validate stewardship outcomes, and automate repeatable profiling, DQ, metadata, and governance activities.
Apply working knowledge of APIs, Git, testing, data engineering practice, and Bronze, Silver, and Gold data foundations to collaborate effectively with technical teams.
Identify automation opportunities and define fit-for-purpose controls and validation for stewardship workflows.
Apply approved GenAI and LLM capabilities, prompt engineering, and AI-assisted workflows to profiling, metadata, cataloging, context generation, and DQ activities.
Review and validate AI-generated recommendations, establish appropriate human oversight for assigned scope, and coach others on responsible use.
Contribute to practical AI-agent and semantic use cases in collaboration with modeling and technology teams.
Apply established GxP, privacy, sensitivity, retention, data-integrity, and permitted-use controls to assigned stewardship scope and escalate policy interpretations when required.
Ensure stewardship evidence and documentation support audit readiness, traceability, and appropriate risk management.
Coach less-experienced stewards, review their deliverables, and support their development against the stewardship skill framework.
Lead training or demonstrations for stewardship tools and practices.
Serve as a key stewardship partner for Data Owners, R&D SMEs, Data Engineering, Data Modeling, Analytics, and governance stakeholders.
Communicate stewardship findings, risks, and decisions clearly to both business and technical audiences.