Senior Specialist , Data Stewardship

Job Description

The DHH Commercial Data Solutions team is seeking a Senior Specialist, Business Rule Management and Data Quality Strategy to advance scalable business rules and data quality capabilities across therapeutic areas, beginning with Oncology. The role will support the design, governance, automation, and operationalization of practices that improve transparency, consistency, and trust in data used for analytics, operations, launches, and business decision‑making.

• Support the strategy, governance, and lifecycle framework for business rule management and data quality within DHH, initially focused on Oncology.
• Partner with cross‑functional stakeholders to translate business needs into defined data rules, quality checks, governance processes, and implementation requirements.
• Create and maintain business rule documentation, including ownership, traceability, versioning, approval workflows, and change management practices.
• Contribute to data quality standards, profiling approaches, issue management processes, root cause analysis, remediation tracking, scorecards, and KPIs.
• Identify opportunities to simplify, automate, and scale business rule and data quality processes through improved workflows, tooling, AI‑enabled capabilities, and reusable operating models.
• Collaborate with data engineering and platform teams to support accurate implementation of business rules and data quality checks within database structures, Databricks, SQL‑based processes, and related data platforms.
• Support change management and adoption activities for upcoming Oncology launches, evolving business needs, and expansion of the model to additional therapeutic areas.
• Communicate data, rule, and quality concepts clearly to both technical and non‑technical stakeholders, including senior business partners.

• Bachelor’s degree in data management, information systems, computer science, business, life sciences, or a related discipline; or equivalent practical experience.
• Relevant experience working with healthcare, life sciences, commercial, clinical, or regulated data environments.
• Experience in business rule management, data quality, data governance, data management, business analysis, or related data strategy work.
• Ability to translate business requirements into data rules, quality checks, governance processes, or automated data management workflows.
• Technical understanding of database structures and data platforms, with practical experience using SQL.
• Experience working with cross‑functional teams and influencing stakeholders without direct authority.
• Effective written and verbal communication skills, including the ability to explain technical and data concepts to non‑technical audiences.
• Strong analytical thinking, problem‑solving, organization, and attention to detail.
• Experience using JIRA or similar tools to manage requirements, workflows, issues, or delivery activities.

• Oncology data experience, including familiarity with launch, commercial, clinical, or patient‑related data use cases.
• Experience with Databricks or similar cloud‑based data platforms.
• Experience designing or scaling business rule repositories, data quality frameworks, stewardship models, scorecards, or governance operating models.
• Familiarity with automation, AI‑enabled data management capabilities, metadata management, data catalog tools, or data lineage concepts.
• Experience partnering with data engineering, analytics, product, or platform teams to implement rule‑based or quality‑driven data solutions.
• Ability to communicate strategy, progress, risks, and recommendations in a clear and executive‑ready manner.

• Data‑driven decision‑making.
• Business and technical translation.
• Process design and continuous improvement.
• Stakeholder collaboration and influence.
• Governance mindset and attention to detail.
• Comfort working in ambiguity and evolving priorities.

• Biological Sciences
• Business Analysis
• Business Rules Modeling
• Computer Science
• Data Governance
• Data Lineage
• Data Management
• Data Modeling
• Data Stewardship
• Issue Management
• Life Science
• Metadata Management
• Quality Management
• Requirements…