The AVP of Data Management is responsible for defining and executing the enterprise data platform strategy, architecture, and engineering roadmap. This leader oversees data integration, quality, and operational reliability while partnering with cross-functional teams to support analytics, AI, and business transformation initiatives.
Job Summary:The Associate Vice President, Data Management is a senior technology executive responsible for the strategy, architecture, engineering, integration, quality, and operational management of enterprise data platforms. This leader ensures that the data ecosystem is scalable, secure, reliable, and capable of supporting analytics, artificial intelligence, operational reporting, regulatory compliance, and business transformation initiatives. They serve as the enterprise owner for a modern data platform strategy, including cloud data platforms, data movement, integration architecture, master data management, operational excellence, and data reliability. The AVP partners closely with Data Strategy & Governance, Data & AI Solutions, Enterprise Architecture, Clinical Operations, Finance, and Technology leaders to ensure the enterprise data foundation enables business outcomes while maintaining appropriate controls, performance, and scalability.
Essential Functions:- Define and execute the enterprise data platform strategy and multi-year technology roadmap.
- Establish architecture standards, design principles, and engineering practices supporting enterprise data initiatives.
- Lead modernization efforts across data platforms, integration technologies, and operational processes.
- Evaluate emerging technologies and industry trends to continuously improve enterprise data capabilities.
- Align data platform investments with organizational priorities, technology strategy, and business objectives.
- Act as executive sponsor for major enterprise data transformation initiatives.
- Lead the creation and governance of enterprise data architecture standards and reference architectures.
- Establish target-state architecture supporting operational reporting, advanced analytics, AI, interoperability, and regulatory requirements.
- Define canonical data models, integration patterns, and enterprise information architecture.
- Partner with Enterprise Architecture to align data strategy with broader application and infrastructure roadmaps.
- Oversee metadata-driven architecture, data lineage, and data lifecycle management practices.
- Drive adoption of modern architectural patterns including lakehouse, event-driven, and domain-oriented data architectures.
- Provide executive leadership for enterprise data engineering teams.
- Oversee design, development, and optimization of scalable ETL/ELT pipelines and data products.
- Ensure engineering delivery practices support reliability, performance, maintainability, and reusability.
- Champion automation, DevOps, and DataOps capabilities across the organization.
- Establish engineering standards, code quality practices, CI/CD frameworks, and operational controls.
- Lead platform optimization efforts to improve performance, scalability, and cost efficiency.
- Own enterprise integration strategy across clinical, operational, financial, and third-party systems.
- Ensure integration solutions align with enterprise standards, regulatory requirements, and business objectives.
- Partner with application and infrastructure teams to streamline system connectivity and data flow.
- Lead large-scale migration and consolidation initiatives during mergers, acquisitions, or platform modernization efforts.
- Establish operational governance and performance management practices for data platforms.
- Ensure platform availability, reliability, resiliency, and service performance meet defined SLAs.
- Lead enterprise data quality monitoring, remediation, and continuous improvement efforts.
- Develop operational metrics, KPIs, dashboards, and reporting frameworks to measure platform health and business value.
- Oversee capacity planning, incident management, root-cause analysis, and problem resolution processes.
- Partner with Data Strategy & Governance leadership to operationalize data quality standards and stewardship practices.
- Ensure appropriate security, access controls, disaster recovery, and risk management processes are in place.
- Build and lead high-performing teams including directors, managers, architects, engineers, and operations professionals.
- Foster a culture of accountability, innovation, operational excellence, and continuous improvement.
- Develop leadership talent and succession planning within the organization.
- Establish organizational priorities, objectives, and performance expectations.
- Lead vendor management, contract negotiations, and strategic technology partnerships.
- Manage budgets for personnel, infrastructure, licensing, and external services.
- Perform any other job related duties as requested.
Education and Experience:- Bachelor's degree in Computer Science, Information Systems, Data Management, Engineering, or a related field required
- Master's degree preferred
- Equivalent years of relevant work experience may be accepted in lieu of required education
- Twelve (12) years of progressive experience in data management, data architecture, data engineering, or platform engineering required
- Five (5) years of leadership experience managing large-scale technology organizations required
- Experience leading enterprise data platforms supporting analytics, operational reporting, and AI initiatives required
- Experience establishing and scaling operational practices for mission-critical data platforms required
- Experience leading cloud-based data modernization initiatives required
Competencies, Knowledge and Skills:- Familiarity with healthcare payer industry strongly preferred
- Knowledge of Databricks, Azure, Snowflake, or comparable modern cloud data platforms
- Familiarity with data mesh, domain-driven architecture, and modern DataOps practices
- Familiarity with healthcare interoperability standards including FHIR, HL7, EDI, and related healthcare data exchanges
- Ability to support AI/ML platforms and large-scale enterprise analytics environments
- Skilled with master data management, metadata management, and data observability solutions
Licensure and Certification:Working Conditions:- General office environment; may be required to sit or stand for extended periods of time
- Travel is not typically required
Compensation range $150,000-$300,000. CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package.
Compensation Type (hourly/salary):
Salary
Organization Level Competencies
Fostering a Collaborative Workplace Culture
Cultivate Partnerships
Develop Self and Others
Drive Execution
Energize and Inspire the Organization
Influence Others
Pursue Personal Excellence
Understand the Business
This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.
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