Associate Director, Data Product Management

AstraZeneca•Gaithersburg, MD

20h•$194,571 - $291,856•Hybrid

About The Position

Are you ready to turn enterprise-scale data into decisions that transform cancer care? As Associate Director, Data Product Management, you will lead how critical data is collected, organized, and shared across our Oncology portfolio to accelerate smarter decisions and measurable impact for patients. Your work will directly help teams bring innovative medicines to people earlier, improve access, and compose the cancer care experience from diagnosis to survivorship. You will operate at the intersection of business, technology, and data—defining a clear strategy, building scalable products, and ensuring our data is trusted, compliant, and easily discoverable. Partnering with commercial leaders, engineering, analytics, and external providers, you will embed a product-minded, agile approach that turns commercial priorities into reusable data assets and insightful outcomes. Can you see yourself creating a roadmap that unlocks value, speeds launches, and enables advanced analytics across the enterprise?

Requirements

Bachelor’s degree; preferably in a relevant field
5+ years of Commercial Data Management and/or related experience
Strong ability to balance critical thinking with execution, operating effectively in complex, fast-paced environments.
Validated experience leading cross-functional teams and influencing across a matrixed organization, with excellent team member management and the ability to drive alignment without direct authority.
Solid product management expertise, including lifecycle ownership, roadmap development, backlog management, and outcome tracking.
Strong analytical and problem-solving capabilities, integrating business, technical, and operational perspectives to deliver scalable solutions in collaboration with engineering teams.
Broad data knowledge spanning data management principles (governance, architecture, modelling, integration, BI), data engineering concepts (data lakes, master/reference data), and agile development methodologies.
Ability to simplify complex concepts and provide clear direction to teams

Nice To Haves

Advanced degree or equivalent experience in a relevant field (e.g., Data Science, Computer Science, Engineering, Business)
Experience with Oncology or broader life sciences commercial data sets (e.g., claims, EHR, prescription, specialty pharmacy, RWE)
Hands-on familiarity with modern cloud data platforms and tooling (e.g., Azure, AWS, GCP, Databricks, Snowflake)
Experience with data catalog and metadata management solutions (e.g., Collibra, Alation) and maintaining lineage at scale
Knowledge of data privacy, security, and compliance frameworks relevant to healthcare (e.g., GDPR, HIPAA) and internal policy controls
Validated enablement of AI/ML use cases and collaboration with analytics and data science teams
Product analytics, indictor frameworks, and value realization tracking for data products
Vendor management and budget ownership across data suppliers and service providers
Relevant certifications in product management, data management, or cloud technologies

Responsibilities

Define the domain-level strategy and north star for Oncology data products aligned to enterprise and commercial priorities; identify high-impact use cases, including AI and advanced analytics, with clear value measures.
Own end-to-end roadmaps from inception through launch, scale, and optimization; manage dependencies across products and platforms; continuously prioritize based on realized value, risks, and evolving business needs.
Lead backlog prioritization; translate business needs into unambiguous technical specifications and data requirements; collaborate with engineering and architecture to manage trade-offs and technical debt.
Serve as primary liaison to commercial partners; articulate value cases and secure alignment on priorities and outcomes; convert market and operational needs into actionable data solutions.
Translate business goals into a structured data roadmap with landmarks; define required internal/external data, acquisition, storage, and processing plans; monitor execution and adjust to demand.
Drive alignment across platforms, architecture, governance, and analytics; champion agile approaches committed to continuous value delivery and shared accountability.
Define and be responsible for scalable ingestion and processing from first- and third-party sources; ensure reliability, timeliness, and accuracy; resolve technical issues and optimize pipelines with engineering teams.
Establish and implement governance, access, and usage controls; approve downstream usage in line with policy and regulation; steward adherence to enterprise standards.
Implement validation strategies for accuracy, completeness, and reliability; standardize definitions, dictionaries, and models; maintain lineage to ensure clarity and trust.
Define catalog requirements; ensure metadata, lineage, and documentation are complete and current; drive adoption among business users for discoverability and self-service.
Build strategic partnerships; lead all aspects of vendors and data suppliers for value, compliance, and performance; run budgets to support business-critical insights.
Collaborate with analysts and data scientists to support advanced analytics; identify and resolve data quality issues impacting insights; enable actionable outcomes in marketing, sales, access, and strategy.
Define product-level indicators and adoption metrics; track value realization; use insights to optimize products and modernize capabilities.
Promote data product adoption and data-driven decision-making; create documentation, training, and enablement; introduce innovative data and AI practices and build skills across the organization.