Own and manage the enterprise integration capability for governed, reusable, and reliable data in Data Cloud.
Convert business and analytics requests into a prioritized data product backlog.
Define and drive reusable integration patterns and shared data products across Data Spaces.
Ensure that data pipelines, data lake objects, data transforms, and reporting models meet enterprise standards.
Stakeholder & Delivery Management:
Partner with commercial, technical, and analytics stakeholders to gather and prioritize requirements.
Coordinate architecture and delivery dependencies with cross-functional teams (architects, engineers, QA, business teams).
Own delivery predictability, pipeline reliability, and data quality metrics.
Facilitate transparent communication of dependencies, risks, and release readiness.
Backlog & Operational Excellence:
Maintain a healthy, prioritized, and testable integration backlog ready for sprint planning.
Oversee incident, defect, and technical debt management, ensuring operational excellence.
Monitor and improve lineage, ownership, and support of data integration assets.
Technical Fluency:
Apply deep knowledge of data integration, APIs, data modeling, data contracts, schema mapping, and observability.
Lead efforts using Salesforce Data Cloud, Snowflake (or similar), Veeva, and CRM integration technologies.
Ensure source-to-target data reconciliation and uphold data completeness, validity, and usability.
Agile & Cross-Functional Leadership:
Lead and coordinate agile delivery teams, aligning business demand with technical execution.
Translate business and analytics needs into technical requirements, balancing architecture trade-offs.
Collaborate effectively across boundaries to deliver collective impact and sustainable solutions.
Compliance & Industry Focus:
Navigate the complexity of regulated, data-intensive environments (pharma, life sciences, etc.).
Ensure compliance with privacy, security, and governance standards.
Continuous Improvement:
Proactively identify opportunities for standardization, reuse, and reduction of duplicative work.
Drive operational excellence through monitoring, support practices, and continuous feedback.