Data Cloud Integration Product Manager

Job Title: Data Cloud Integration Product Manager Location: East Hanover, NJ Duration: 12 months Pay Range: $(80.00 – 100.00)/hr on W2 all-inclusive without benefits Hybrid: 3 days onsite, 2 days remote Job Description: Client is on a mission to transform medicine and improve lives worldwide. As a global leader in healthcare, we leverage advanced technology and data to deliver patient-centric solutions, enhance customer engagement, and drive innovation. We collaborate closely with the US business, bringing insights and challenging ideas to empower smarter, data-driven decision-making. The US CRM organization sits within Strategy, Platforms prepare Data Stream, Data Lake Object, and Enterprise Analytics Space mappings for PI planning. Establish reusable patterns: Partner with architects and the IT Center of Excellence to define common ingestion, transformation, error-handling, observability, testing, and deployment patterns. Coordinate cross-space dependencies: Align enterprise Data Cloud work with Data Space Product Owners, source-system owners, governance, architecture, analytics, and scrum teams; surface sequencing and capacity trade-offs. Lead build and lifecycle management: Guide the development and ongoing maintenance of Data Streams, Data Lake Objects, batch data transforms, and cross-space calculated insights from design through production support. Assure data quality and reliability: Define and validate data quality, reconciliation, lineage, refresh, monitoring, and operational support expectations for shared integrations. Measure and communicate performance: Track pipeline delivery health, reliability, reuse, data quality, and adoption; communicate risks, decisions, and outcomes to platform leadership and stakeholders. Key Performance Indicators: KPI area What good looks like Delivery predictability Committed integration scope is delivered with transparent dependencies, risks, and release readiness. Pipeline reliability Shared data pipelines meet agreed refresh, stability, monitoring, and support expectations. Data quality Source-to-target data is reconciled and meets defined completeness, validity, and usability criteria. Reuse and standardization Enterprise patterns and shared data products reduce duplicative integration work across Data Spaces. Backlog health Integration work is prioritized, clearly specified, testable, and ready for sprint and PI planning. Operational excellence Incidents, defects, technical debt, lineage, and ownership are visible and actively managed. Ideal Background: Bachelor's degree in data, technology, business, engineering, computer science, or a related field required; advanced degree preferred. Fluent English; other languages are desirable. 5+ years of product management, data integration, data engineering, platform delivery, or technical product ownership experience. Strong knowledge of data integration concepts, APIs, batch and streaming pipelines, transformation, data contracts, schema mapping, lineage, observability, and data quality. Hands-on understanding of Salesforce Data Cloud, including Data Streams, Data Lake Objects, data modeling, identity resolution dependencies, calculated insights, and activation workflows. Demonstrated experience leading an agile backlog and coordinating delivery across architects, engineers, analysts, QA, source-system owners, and business product teams. Strong ability to translate business and analytics needs into scalable technical requirements and explain architecture trade-offs to nontechnical stakeholders. Preferred Experience with Salesforce, Snowflake or comparable cloud data platforms, Veeva, CRM integration, and enterprise analytics ecosystems. Familiarity with CI/CD, DevOps, metadata management, data cataloging, and production support practices. Background in pharma, life sciences, or another regulated, data-intensive industry. Leadership Competencies Navigate complexity: Enable impactful and timely decision-making across business, data, technology, privacy, and compliance stakeholders. Identify the critical issues in complex situations, maintain focus on enterprise outcomes, and adapt priorities as conditions change. Take a long-term view of platform sustainability, downstream impacts, and reusable enterprise capabilities. Deliver collective impact Integrate diverse perspectives to achieve the best outcome for the enterprise. Influence without authority and collaborate effectively across organizational boundaries. Challenge assumptions constructively and make decisions grounded in evidence.