Product Manager - Data Management & Data Products

IntegriChain • Philadelphia, PA

23h • 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 owns the roadmap and requirements for capabilities that ingest, standardize, integrate, govern, enrich, and deliver high-quality data across the ICyte platform. The Product Manager works with customers, subject-matter experts, engineering, and internal stakeholders to understand complex data and business problems and translate them into scalable product direction and measurable outcomes.

The role spans enterprise data integration and quality, governance, reference and master data, and the creation of reusable, analytics- and AI-ready data assets. It also supports Life Sciences data requirements, including areas such as Chargebacks, Government Pricing, contracts, claims, sales, customer, and reference data. The Product Manager partners with engineering and QA throughout Agile delivery and coordinates requirements, prioritization, testing, release readiness, documentation, rollout, and post-release feedback.

IntegriChain offers a hybrid working environment. Employees in this role are expected to visit office locations quarterly or a few times per quarter for workshops, team meetings, and collaboration. The company is headquartered in Philadelphia, Pennsylvania, with additional offices in Ambler, Pennsylvania; Pune, India; and Medellín, Colombia.

Requirements

• At least 7 years of experience in Product Management, Product Ownership, Business Analysis, or Data Product Management, preferably with enterprise data products or platforms.
• Demonstrated ownership of product roadmaps, requirements, backlogs, prioritization, and delivery of complex technology products.
• Experience in one or more of the following: enterprise data platforms; data integration, ETL, or ELT; data warehousing; data quality; data governance; reference or master data; analytics or reporting data products; metadata or semantic layers.
• Ability to translate business problems into clear data and technical requirements without personally implementing the engineering solution.
• Experience partnering effectively with Data Engineering, Software Engineering, QA, Analytics, and business or domain teams.
• Strong understanding of how data moves from source systems through transformation and quality processes into operational, reporting, analytics, or AI applications.
• Experience working in Agile/Scrum environments and managing product delivery with 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 business and technical audiences.

Nice To Haves

• Experience with Life Sciences, healthcare, pharmaceutical commercial data, Market Access, or Net Revenue.
• Familiarity with healthcare organization or 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 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 investment with customer needs, product strategy, and business objectives.
• Partner with customers, domain subject-matter experts, 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 business entities and reference or master data, including identity resolution, matching, hierarchies, relationships, and mastered records where appropriate.
• Enable reusable, well-defined data assets, semantic models, and governed data products for reporting, analytics, and AI applications.
• Work with domain teams to understand Life Sciences data requirements across Chargebacks, Government Pricing, contracts, claims, sales, customer, and reference data.
• Support productization and integration of Life Sciences datasets and identifiers, including 844, 867, 852, HIN, DEA, NPI, NCPDP, and 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; proactively manage 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.
• Non-medical perks, including Flexible Paid Time Off.
• Learning and Development opportunities, including access to over 700 development courses free to employees.

What This Job Offers

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