Associate Director, Data Enablement & Operations - Patient Services & Value & Access

Title: Associate Director, Data Enablement & Operations - Patient Services & Value & Access Company: Ipsen Biopharmaceuticals Inc. About Ipsen: Ipsen is a mid-sized global biopharmaceutical company with a focus on transformative medicines in three therapeutic areas: Oncology, Rare Disease and Neuroscience. Supported by nearly 100 years of development experience, with global hubs in the U.S., France and the U.K, we tackle areas of high unmet medical need through research and innovation. Our passionate teams in more than 40 countries are focused on what matters and endeavor every day to bring medicines to patients in 88 countries. We build a workplace that champions human-centric leadership and fosters a culture of collaboration, excellence and impact. At Ipsen, every individual is empowered to be their true selves, grow and thrive alongside the company’s success. Join us on our journey towards sustainable growth, creating real impact on patients and society! For more information, visit us at https://www.ipsen.com/ and follow our latest news on LinkedIn and Instagram . Job Description: The Associate Director, Data Enablement & Operations - Patient Services & Value & Access is the hands-on data engineering and operations lead responsible for building, integrating, and running trusted data products that support Patient Services and Value & Access. The role owns data aggregation, ingestion, transformation, quality, and analytics enablement across internal platforms and external partner feeds. This individual serves as the primary data point of contact for Patient Services and Value & Access, partnering with business stakeholders, Data Strategy & Analytics, technology teams, Salesforce platform owners, and vendors. The role translates business and reporting needs into scalable pipelines, curated datasets, governed metrics, and dependable operational processes using Snowflake, Databricks, SQL, and Python. The successful candidate personally develops, tests, troubleshoots, documents, and supports production solutions. Main Responsibilities & Technical Competencies Data Engineering & Pipeline Development Design, build, test, deploy, and maintain scalable batch and near-real-time pipelines using Snowflake, Databricks, SQL, Python, and approved orchestration tools. Develop ingestion and transformation workflows for Hub, specialty pharmacy, specialty distributor, payer, CRM, claims, and access-related data. Create reusable frameworks, source-to-target mappings, data models, and automated validation controls. Optimize pipelines, queries, storage, and compute for performance, reliability, maintainability, and cost. Perform hands-on root-cause analysis and code remediation for failed jobs, defects, reconciliation issues, and downstream impacts. Patient Services & Value & Access Data Enablement Serve as the primary data enablement and aggregation point of contact for Patient Services and Value & Access. Translate business workflows and reporting needs into analytics-ready data products and technical specifications. Enable data supporting patient enrollment, access progression, benefits verification, prior authorization, affordability, fulfillment, and adherence. Aggregate and harmonize data across brands, programs, vendors, and channels with appropriate controls for sensitive data. Define data acceptance criteria, refresh expectations, reconciliation rules, and service levels with business owners. Salesforce Life Sciences Cloud & Integration Understand Salesforce Life Sciences Cloud data structures, workflows, integration events, and downstream requirements. Design and support interfaces among Salesforce Life Sciences Cloud, Hub and specialty pharmacy partners, Snowflake, Databricks, and reporting platforms. Validate completeness, accuracy, timeliness, and traceability of inbound and outbound Salesforce feeds. Assess downstream impact of CRM releases and coordinate required pipeline or model changes. Analytics Enablement & Data Products Partner with Data Strategy & Analytics to provide certified datasets, governed metrics, semantic-ready data, and documented business logic. Convert recurring analytical requirements into durable data models rather than one-time extracts. Support controlled SQL/Python analysis while industrializing repeatable needs. Enable traceability from source through transformations to reports, metrics, and analytical outputs. Collaborate with analysts and data scientists on feature-ready datasets and productionization of approved logic. Data Quality, Governance & Compliance Implement automated controls for completeness, accuracy, validity, timeliness, duplication, referential integrity, and reconciliation. Own monitoring, issue triage, incident resolution, runbooks, lineage, technical documentation, and audit evidence. Apply role-based access, least privilege, privacy, retention, and approved-use requirements. Partner with Privacy, Legal, Compliance, Security, and platform teams in a regulated environment. Communicate data risks, root cause, remediation, and recurrence-prevention actions. Operating Model, Delivery & Vendor Management Manage intake and prioritization of requests, enhancements, defects, and new-source onboarding. Coordinate internal teams and external vendors with clear requirements, dependencies, acceptance criteria, and service expectations. Monitor feed health, delivery timeliness, quality trends, incidents, and backlog status. Maintain code in approved repositories and enforce testing, release, version-control, and documentation standards. Build reusable capabilities that reduce manual effort, vendor dependency, and onboarding time. Success Measures Reliable and timely delivery of trusted Patient Services and Value & Access data products. Reduced manual aggregation and one-time pulls through reusable pipelines and curated datasets. Improved data quality, reconciliation coverage, lineage, documentation, and issue-resolution time. Faster onboarding of vendors, programs, brands, feeds, and analytical use cases. Adoption of certified datasets and governed metrics by analytics and reporting teams. HOW - Knowledge & Experience Knowledge & Experience (essential): Bachelor's degree in a technical or analytical field, or equivalent practical experience. 12+ years in data engineering, enablement, operations, or analytics engineering, including hands-on development. Advanced SQL and Python skills with production pipeline experience. Hands-on Snowflake and Databricks experience across ingestion, transformation, orchestrati