Senior Director, Data Product and Enablement

At SCP Health, what you do matters

As part of the SCP Health team, you have an opportunity to make a difference. At our core, we work to bring hospitals and healers together in the pursuit of clinical effectiveness. With a portfolio of over 8 million patients, 7500 providers, 30 states, and 400 healthcare facilities, SCP Health is a leader in clinical practice management spanning the entire continuum of care, including emergency medicine, hospital medicine, wellness, telemedicine, intensive care, and ambulatory care.

• Strong track record of providing excellent work/life balance.

• Comprehensive benefits package and competitive compensation.

• Commitment to fostering an inclusive culture of belonging and empowerment through our core values - collaboration, courage, agility, and respect.

• Lead, mentor, and grow a multi-disciplinary team spanning data acquisition, data engineering, data governance, data product management, and business analysis functions.

• Define clear performance goals, career development paths, and succession planning for direct and indirect reports.

• Foster a culture of accountability, continuous learning, collaboration, and psychological safety.

• Partner with HR and Talent Acquisition to attract and retain top data talent.

• Drive organizational design and team structure to scale with evolving business needs.

• Oversee the ingestion of diverse clinical data sources from EMRs at client facilities.

• Develop and maintain a scalable, reliable, and auditable data acquisition framework supporting both real-time and batch pipelines.

• Partner with clinical, IT, and vendor teams to negotiate and implement data exchange agreements (HL7, FHIR, EDI, APIs).

• Own the end-to-end SLA management of clinical data feeds, ensuring accuracy, completeness, and timeliness.

• Define and own the data product strategy, establishing a product-oriented operating model that treats curated clinical data assets as reusable, discoverable, and trusted products consumed across analytics, AI/ML, and operational teams.

• Build, lead, and grow a Business Analysis team responsible for partnering with clinical, operational, and technology stakeholders to elicit, document, and prioritize data and reporting requirements.

• Establish and standardize business analysis practices including use case documentation, business requirements documents (BRDs), functional specifications, user stories, and acceptance criteria to support data product and pipeline delivery.

• Ensure BAs serve as the connective tissue between business stakeholders and technical delivery teams - translating clinical and operational needs into clear, actionable data requirements for engineering and product squads.

• Lead the design, development, and lifecycle management of clinical data products - ensuring they are well-documented, SLA-backed, and aligned to business and clinical use cases.

• Collaborate with clinical, operational, and technology stakeholders to prioritize the data product roadmap based on value, feasibility, and strategic impact.

• Establish data product KPIs - including adoption, quality scores, latency, and consumer satisfaction - and drive continuous improvement through feedback loops with internal and external stakeholders.

• Lead the architecture and development of modern data pipelines and integration platforms for acquiring clinical data feeds from facilities.

• Champion cloud-native, scalable data infrastructure (e.g., Snowflake, AWS, dbt) and modern data stack best practices.

• Drive the adoption of Data Ops principles: CI/CD for data pipelines, automated testing, observability, and lineage tracking.

• Establish and enforce enterprise data governance policies, standards, and frameworks aligned with regulatory requirements (HIPAA, 21 CFR Part 11, GDPR where applicable).

• Lead data stewardship initiatives including data cataloging, metadata management, data quality rules, and master data management.

• Build and chair cross-functional data governance forums to align stakeholders on data definitions, ownership, and usage standards.

• Drive accountability for data quality KPIs and remediation workflows across source systems and integration layers.

• Champion an AI-first automation mindset across all data acquisition and integration workflows - from intelligent data mapping to anomaly detection and self-healing pipelines.

• Identify and lead strategic initiatives to modernize legacy clinical data feed processes using AI/ML, NLP, and intelligent automation tools.

• Partner with technology and innovation teams to evaluate and implement emerging technologies that accelerate data pipeline efficiency and reduce manual intervention.

• Develop a multi-year roadmap for the modernization of the clinical data ecosystem, with measurable milestones and business outcomes.

• Serve as the…