AVP, Enterprise Data Platforms at Mosaic Health

Fort Myers, Florida, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Jul, 26

Salary

273819.0

Posted On

20 Apr, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Databricks, Data Engineering, Data Governance, Data Architecture, Machine Learning, Artificial Intelligence, Business Intelligence, SQL, Python, Tableau, Power BI, Cloud Computing, Healthcare Analytics, Leadership, Strategic Planning, Data Modeling

Industry

Hospitals and Health Care

Description

Job Description Summary ‎ Mosaic Health is seeking an Associate Vice President of Enterprise Data Platforms to own the full data technology stack across the organization and serve as the senior leader accountable for how data is engineered, governed, analyzed, and activated to drive clinical, financial, and operational decisions. This is a high-visibility, high-impact role at the intersection of enterprise technology strategy and the analytic outcomes that shape care delivery and business performance. The foundational platform for this role is Databricks — Mosaic’s cloud-based platform that unifies data engineering, data science, and machine learning and AI on a single collaborative infrastructure. The AVP is responsible for the enterprise-wide implementation, optimization, and governance of Databricks as the backbone of Mosaic’s data strategy, enabling teams across the organization to process large datasets, build AI and ML models, and generate business intelligence using SQL & Python. Reporting to the VP of Information Technology, the AVP leads three Directors: one overseeing the enterprise data warehouse, one leading data architecture and governance, and one accountable for data analytics and business intelligence including clinical analytics. The AVP partners closely with finance, clinical, and analytics leaders across Mosaic’s business units to ensure the data platform translates raw data into trusted, actionable insight. ‎ How will you make an impact & Requirements ‎ Key Responsibilities Enterprise Data Platform Strategy Own and advance the enterprise data platform strategy, with Databricks as the foundational platform unifying data engineering, data science, and ML/AI across Mosaic Health Define the roadmap for platform maturity, including adoption of Databricks capabilities such as Unity Catalog, Delta Lake, MLflow, and Mosaic AI tooling Ensure the data platform strategy is aligned to Mosaic’s clinical, financial, and operational priorities and can scale with organizational growth and acquisition activity Evaluate emerging data technologies and make informed recommendations on adoption to senior IT and business leadership Databricks Platform Ownership Lead the enterprise-wide implementation, optimization, and governance of Databricks as Mosaic’s cloud-based platform Ensure Databricks is leveraged as a unified, collaborative environment for data engineering, data science, machine learning, AI model development, and business intelligence Oversee platform performance, cost optimization, access controls, and workspace governance across Databricks environments Build organizational fluency in Databricks capabilities across SQL, Python, R, and Scala to maximize platform value across technical teams Data Architecture & Governance Partner with the Director of Data Architecture to ensure Mosaic’s lakehouse architecture is well-designed, documented, and evolving in step with the data strategy Champion enterprise data governance — ensuring data quality, consistency, lineage, and security standards are established, maintained, and embedded in how data is produced and consumed Ensure data governance policies meet regulatory and compliance requirements applicable to healthcare data, including HIPAA and applicable state requirements Drive the adoption of data governance practices across business units and clinical teams, positioning data as a trusted organizational asset Data Engineering & Pipeline Delivery Lead Mosaic Health’s enterprise data engineering agenda, including the design, build, and operation of scalable, secure, and reliable data pipelines that ingest, transform, and curate clinical, financial, and operational data for analytics, reporting, and AI/ML use cases. Establish modern engineering standards across Databricks for batch and near-real-time processing, orchestration, testing, observability, documentation, and code promotion, while driving performance, cost efficiency, and platform reliability. Ensure reusable data models, disciplined pipeline governance, and strong delivery practices are in place so Mosaic can integrate new data sources quickly, support acquisition-related onboarding, and provide trusted data products at enterprise scale. Analytics, BI & Clinical Intelligence Partner with the Director of Data Analytics & BI to ensure Mosaic’s analytics capabilities — including Tableau and Power BI — deliver trusted, actionable insight to clinical, financial, and operational decision-makers Ensure clinical analytics capabilities are purpose-built to support care quality, patient outcomes, population health, and operational efficiency goals Champion a self-service analytics culture where business and clinical leaders can access and interrogate data with confidence in its accuracy Maintain awareness of the broader data analytics and visualization landscape and guide Mosaic’s tool strategy accordingly Business Partnership & Data Activation Serve as the senior data technology partner to finance, clinical, and analytics leaders across Mosaic’s business units, translating complex data capabilities into business value Partner with clinical leadership to ensure data platforms and analytics capabilities support care delivery, quality improvement, and value-based care initiatives Partner with finance leadership to ensure the data platform supports financial planning, reporting, and performance management needs Ensure data products and analytics outputs are well understood, trusted, and actively used by decision-makers across the organization Machine Learning & AI Lead the enterprise’s approach to ML and AI development within the Databricks environment, including model development, deployment, and lifecycle management Partner with clinical and operational leaders to identify and prioritize AI and ML use cases that can improve care delivery, operational efficiency, and financial performance Ensure ML and AI initiatives are governed responsibly, with appropriate validation, bias review, and performance monitoring in place Build or recruit data science and ML engineering talent capable of delivering production-grade AI outcomes on the Databricks platform Team Leadership & Development Lead, develop, and hold accountable three Directors responsible for the enterprise data warehouse, data architecture and governance, and data analytics and BI Set a clear strategic direction for the data platforms organization and create conditions for each team to execute with excellence Build a data organization culture defined by rigor, curiosity, partnership with the business, and a commitment to data quality and trust Develop internal talent and build organizational capability across data engineering, architecture, analytics, and data science disciplines Governance, Security & Compliance Ensure all data platforms and pipelines operate in compliance with HIPAA and applicable healthcare data regulations Partner with IT Security to maintain appropriate data access controls, encryption standards, and audit capabilities across the data stack Establish and maintain data retention, classification, and lifecycle management policies across the enterprise data environment Qualifications Experience 10+ years of progressive experience in enterprise data, analytics, or data platform leadership, with at least 5 years in a senior leadership role managing data teams and Directors Deep, hands-on experience with Databricks as an enterprise platform — including data engineering, ML/AI workloads, and platform governance Demonstrated experience owning a full enterprise data technology stack across warehousing, architecture, and analytics in a complex, data-intensive organization Proven experience building and leading data engineering organizations responsible for ingestion, ETL/ELT, orchestration, data modeling, and production data reliability in a modern cloud or lakehouse environment. Experience in architecting data pipelines using tools and frameworks like Databricks Workflows, Azure Data Factory, Azure Synapse, Spark / Spark Streaming, Azure functions, Airflow, dbt, Python, and SQL Experience with modeling, querying, and optimization for columnar database technologies (e.g., Snowflake, BigQuery, Redshift), NoSQL database technologies (e.g., DynamoDB, BigTable, Cosmos DB, etc.), relational database systems (e.g., SQL Server, Oracle, MySQL), and data lakes and data lake storage technologies (e.g. Azure Data Lake, Delta Lake)Experience delivering analytics and BI capabilities to clinical, financial, and operational stakeholders in a healthcare or similarly regulated environment Experience with Tableau and Power BI at an enterprise scale, with familiarity across the broader data visualization and analytics tool landscape Proven experience building and leading data governance programs including data quality, lineage, metadata management, and policy enforcement Knowledge of test plan creation and test programming using automated testing frameworks, data validation and quality frameworks, and data lineage tools Preferred Experience Experience in a large healthcare organization with exposure to clinical data, EHR data integration, population health analytics, or value-based care reporting Experience leading or maturing a lakehouse or data mesh architecture strategy Familiarity with Delta Lake, Unity Catalog, MLflow, or Databricks Mosaic AI tooling Experience with cloud data platforms in AWS, Azure, or GCP environments Background in data science or ML engineering, with the ability to guide ML platform strategy and evaluate model quality Technical Fluency Proficiency or strong working knowledge in SQL and Python as used in data engineering and analytics contexts Working knowledge of data warehousing concepts, lakehouse architecture patterns, ETL/ELT pipeline design, and data modeling Familiarity with HIPAA data handling requirements and enterprise data security standards Ability to engage technically with data engineers, architects, data scientists, and BI developers — setting standards, reviewing designs, and resolving architectural questions Skills & Competencies Executive presence and the ability to communicate complex data concepts clearly to clinical, finance, and senior business leadership audiences Strong business partnership instincts — this leader earns credibility with business and clinical stakeholders by delivering insight they trust and can act on Ability to lead through Directors: setting direction, delegating with confidence, and holding domain leaders accountable to a high standard Comfort operating at both the strategic and technical level — setting platform direction without losing the ability to engage meaningfully on architecture and design Commitment to data quality and governance as a foundational discipline, not an afterthought ‎ Compensation: $182,545.00 to $273,819.00 Beware of fraudulent job postings: While Mosaic Health job advertisements may be found on many sites, our current openings page and its associated Workday account are the only places we accept applications for open roles. If you suspect a job post is fraudulent, please let us know at recruiting@apree.health. Mosaic Health is a national care delivery platform focused on expanding access to comprehensive primary care for consumers with coverage across Commercial, Individual Exchange, Medicare, and Medicaid health plans. Learn More about Mosaic Health Learn More about Millennium Physician Group Learn More about CareMore Health Learn More about Castlight Health Learn More about Vera Whole Health

Responsibilities

The AVP of Enterprise Data Platforms will own the full data technology stack and lead the strategy for data engineering, governance, and analytics. They will manage three directors to ensure data is effectively activated to support clinical, financial, and operational decision-making.