Pharmacy Data Steward

NOTE: This role is Operations side, Business-facing, and non-technical. They need a true Operations side Data Steward with experience with and deep understanding of Pharmacy data. See highlighted areas below. This role will:

• Serve as Data Steward as part of an Agile team dedicated to Pharmacy data operations & initiatives
• Lead Data Governance collaborations with Government stakeholders to document, define, maintain, and manage data standards and assets.

Location: REMOTE

MUST HAVES:

• 5+ years of experience as an Operational Data Steward with Pharmacy Services or healthcare insurer / payer client experience
• 5+ years for experience Deep understanding of Pharmacy Data and Business Operations and Data Standards and interacting with Business-Facing Stakeholders
• 5+ years of experience enforcing and optimizing Data dictionaries, data glossaries, data lineage, data policies, standards, and rules in real-time , across different data systems and sources.
• Excellent verbal and written communication skills .
• Experience in Agile Methodology and tools (e.g., Jira, Rally, etc.)
• Intermediate to Advanced data analysis skills and tools (e.g., SQL, SAS, Python, Hadoop, Teradata, Snowflake, Tableau, Collibra, Infosphere, Alation, etc.)

Role Summary
The Pharmacy Data Steward is a member of a cross-functional Data Governance team who partners with business, technical, and regulatory partners to ensure the documentation and implementation of data standards. The Data Steward leads complex, cross-organizational conversations - including risk assessment, data quality auditing, issue management, and knowledge management - to ensure Pharmacy data is fit for organization use. Candidates should have a strong data management background understanding how data is organized and relationships maintained between data domains across multiple enterprise system with a strong drive towards improving data quality and governance.


This role will focus on optimizing already established data governance policies and practices....Improved execution and monitoring ("operational") vs "green field" or new implementation of Data stewardship/ Governance design).



Responsibilities

• Serves as Data Steward as part of an Agile team dedicated to Pharmacy data operations & initiatives
• Leads Data Governance collaborations with Government stakeholders to document, define, maintain, and manage data standards and assets.
• Assesses and monitors data quality metrics, analyzing trends and proactively promoting remediation and preventive action efforts.
• Partners with IT and business teams to ensure the use of best practices and compliance with data standards.
• Provides consultative stewardship services to delivery and issue resolution teams, serving as subject matter expert as needed.
• Provides guidance on development, usage, and inventory of technical assets.
• Represents Data Governance in enterprise workgroups and data steward communities of practice.

Qualifications:

Business Operations

1. Data Integration:
   • Example: Integrating prescription data from various pharmacies into a centralized database to provide a comprehensive view of patient medication histories.
   • Task: Collaborate with IT teams to develop ETL (Extract, Transform, Load) processes that ensure accurate and timely data integration.
2. Data Analysis:
   • Example: Analyzing drug utilization data to identify trends in medication adherence and potential areas for intervention.
   • Task: Use analytical tools and techniques to generate reports and dashboards that support decision-making for pharmacy benefit management.
3. Claims Processing:
   • Example: Ensuring the accuracy of pharmacy claims data to facilitate timely reimbursement and reduce fraud.
   • Task: Implement validation rules and automated checks to detect anomalies and discrepancies in claims submissions.
4. Formulary Management:
   • Example: Maintaining up-to-date formulary data to ensure that covered medications are accurately reflected in the benefit plan.
   • Task: Work with clinical teams to update formulary lists based on new drug approvals, clinical guidelines, and cost-effectiveness analyses.

Data Standards Perspective:

1. Data Quality Assurance:
   • Example: Establishing data quality metrics for prescription data, such as completeness, accuracy, and timeliness.
   • Task: Develop and implement data quality monitoring processes to regularly assess and improve data quality.
2. Data Governance:
   • Example: Defining data governance policies to ensure consistent handling of pharmacy data across the organization.
   • Task: Create and enforce data governance frameworks that outline roles, responsibilities, and procedures for data management.
3. Standardization:
   • Example: Standardizing data formats for drug utilization data to facilitate interoperability with other healthcare systems.
   • Task: Adopt industry standards such as NCPDP (National Council for Prescription Drug Programs) for data exchange and ensure compliance with these standards.
4. Compliance and Security:
   • Example: Ensuring that patient outcomes data is handled in compliance with HIPAA (Health Insurance Portability and Accountability Act) regulations.
   • Task: Implement data security measures and conduct regular audits to protect sensitive patient information and ensure regulatory compliance.

• 5+ years professional work experience in enterprise level Data Stewardship , Data Governance, Data Management and Data Quality practices
• Strong communications skills ; written, verbal and presentation
• Self-driven and able to function with minimal direction
• Has the ability to engage business and data stakeholders to resolve questions or issues
• Must have the ability to handle multiple and sometimes competing priorities in a fast-paced environment
• Must be able to think creatively, innovate and flex where needed - quick/adaptive learner and collaborator/team player
• Must have strong analytical and problem-solving capabilities
• Able to strategize across complex, cross-functional projects and initiatives
• Experience in Agile Methodology and tools (e.g., Jira, Rally, etc.)
• Intermediate to Advanced data analysis skills and tools (e.g., SQL, SAS, Python, Hadoop, Teradata, Snowflake, Tableau, Collibra, Infosphere, Alation, etc.)
• Bachelor's degree or higher