Product Manager - Data Management & Data Products

IntegriChain • Philadelphia, PA

8h • Hybrid

About The Position

IntegriChain is seeking an experienced Product Manager to define and deliver enterprise data management and data product capabilities for its Life Sciences solutions. The role involves owning the roadmap and requirements for capabilities that ingest, standardize, integrate, govern, enrich, and deliver high-quality data across the ICyte Platform. The ideal candidate will have experience in enterprise data platforms, data products, data integration, data quality, data governance, reference/master data, or analytics-ready data assets. This position requires understanding complex business and data problems, collaborating with technical teams on scalable solutions, and translating these into product strategy, epics, features, user stories, and measurable outcomes. While experience with Life Sciences, healthcare, Net Revenue, or commercial data is beneficial, the primary focus is on a strong, data-oriented Product Manager capable of learning the domain and driving product direction.

Requirements

• 7+ years of experience in Product Management, Product Ownership, Business Analysis, or Data Product Management, preferably working with enterprise data products or platforms.
• Demonstrated ownership of product roadmaps, requirements, backlogs, prioritization, and delivery of complex technology products.
• Experience working with one or more areas such as: Enterprise data platforms, Data integration / ETL / ELT, Data warehousing, Data quality, Data governance, Reference or master data, Analytics / reporting data products, Metadata or semantic layers.
• Ability to translate business problems into clear data and technical requirements without needing to be the engineer implementing the solution.
• Experience partnering effectively with Data Engineering, Software Engineering, QA, Analytics, and business/domain teams.
• Strong understanding of how data moves from source systems through transformation and quality processes into operational, reporting, analytics, or AI applications.
• Proven ability to work in Agile/Scrum environments and manage product delivery using tools such as JIRA and Confluence.
• Strong analytical, problem-solving, documentation, and stakeholder-management skills.
• Excellent written and verbal communication skills, with the ability to communicate effectively with both business and technical audiences.

Nice To Haves

• Experience with Life Sciences, healthcare, pharmaceutical commercial data, Market Access, or Net Revenue.
• Familiarity with healthcare organization/customer data and industry identifiers such as HIN, DEA, NPI, NCPDP, 340B, 844, 852, or 867.
• Experience with Snowflake, dbt, modern cloud data platforms, data warehouses, semantic models, or analytics data products.
• Exposure to Master Data Management or reference data solutions such as Reltio, Informatica MDM, Veeva Network, OneKey, or similar platforms.
• Familiarity with concepts such as entity resolution, matching, hierarchies, relationships, survivorship, and data stewardship.
• Experience supporting governed data assets used by analytics, machine learning, or generative AI applications.
• Experience working with distributed onshore/offshore engineering teams.

Responsibilities

• Own and evolve the product roadmap for enterprise data management and data products, aligning investments with customer needs, product strategy, and business objectives.
• Partner with customers, domain SMEs, engineering teams, and internal stakeholders to identify data challenges and validate problems before defining solutions.
• Define capabilities for acquiring, integrating, standardizing, enriching, governing, and publishing data for operational, analytics, AI, and reporting use cases.
• Translate business and data problems into epics, features, user stories, acceptance criteria, process flows, and data requirements for engineering teams.
• Partner with Data Engineering on ingestion, ETL/ELT, source-to-target mappings, transformations, validation, reconciliation, and downstream data delivery.
• Define product requirements for data quality, validation, lineage, metadata, reference data, stewardship, monitoring, and governance.
• Support capabilities for managing critical business entities such as healthcare organizations, customers, outlets, products, and other reference/master data, including identity resolution, matching, hierarchies, relationships, and mastered records.
• Enable reusable, well-defined data assets, semantic models, and governed data products to support reporting, analytics, and AI applications.
• Work with domain teams to understand data requirements in areas such as Chargebacks, Government Pricing, contracts, claims, sales, customer, and reference data.
• Support productization and integration of Life Sciences datasets and identifiers (e.g., 844, 867, 852, HIN, DEA, NPI, NCPDP, 340B).
• Facilitate prioritization across stakeholders based on business value, customer impact, technical dependencies, data quality, risk, and strategic alignment.
• Partner with Engineering and QA through backlog refinement, sprint planning, estimation, testing, and delivery, managing risks and dependencies.
• Define acceptance criteria and test scenarios, coordinate UAT, and ensure traceability between requirements and delivered capabilities.
• Lead workshops and working sessions across Product, Engineering, Data Science, Analytics, Operations, customer-facing teams, and leadership.
• Drive release readiness, documentation, rollout communication, adoption, and post-release feedback.

Benefits

• Excellent and affordable medical benefits
• Flexible Paid Time Off
• Robust Learning & Development opportunities including over 700+ development courses free to all employees

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed