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.
Why you will love working here:
- 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.
Team Leadership & People Management
- 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.
Data Acquisition & Integration
- 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.
Data Product Management
- 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.
Data Engineering
- 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 DataOps principles: CI/CD for data pipelines, automated testing, observability, and lineage tracking.
Data Governance & Stewardship
- 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.
AI-Driven Modernization & Automation
- 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.
Cross-Functional & Executive Stakeholder Engagement
- Serve as the primary senior liaison for clinical data strategy with externa stakeholders including client IT teams as well as internal stakeholders including Business Development, Business Operations, Legal, Compliance, and executive leadership.
- Present data strategy, program status, risk, and roadmap updates to executive leadership teams
- Drive alignment across product, technology, and clinical functions on shared data standards and integration priorities.
Required Qualifications
- Bachelor’s degree in Computer Science, Information Systems, Biomedical Informatics, or a related technical field; advanced degree (MS, MBA) preferred.
- 15+ years of progressive experience in data management, data engineering, or clinical informatics, with at least 5 years in senior people leadership roles.
- Demonstrated experience managing large, distributed technical teams (10+ direct/indirect reports) in a fast-paced healthcare or life sciences environment.
- Deep expertise in clinical data standards and interoperability frameworks (HL7 FHIR, HL7 v2, SNOMED CT, ICD-10, LOINC).
- Knowledge of modern data engineering tools and platforms (e.g., dbt, Airflow, Snowflake, or equivalent).
- Proven track record of designing and delivering enterprise-scale data governance programs in regulated healthcare environments.
- Strong understanding of healthcare data privacy regulations (HIPAA, 21 CFR Part 11) and their operational implications.
- Experience with AI/ML integration into data pipelines and a clear point of view on applying AI to automate and modernize data workflows.
- Exceptional communication skills with the ability to translate complex technical concepts to executive and non-technical audiences.
Preferred Qualifications
- Experience in clinical trials, pharmacovigilance, or real-world evidence data environments.
- Familiarity with FAIR data principles and federated data architectures.
- Certifications in cloud platforms (AWS, Azure, GCP) or data management (CDMP, TOGAF).
- Experience with vendor management and third-party data ecosystem negotiations.
- Exposure to generative AI platforms and large language model (LLM) use cases for clinical data processing.
Pay Range:
129,751.00 - 199,749.00 USD annually
This range represents the anticipated base salary for this role. Actual compensation will be determined based on experience, qualifications, and internal equity considerations.
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We offer a comprehensive benefits package designed to support your health, financial well-being, and work-life balance, including medical dental, vision insurance, a 401(k) plan with a company match, paid time off and holidays, professional development support, and employee wellness resources.
Visit our website for further information. https://myscpbenefits.com/
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