Chief Data Officer - (Job ID 3419)

Kanini Software Solutions
Nashville, TN, United States
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Data Analysis Cloud Database Continuous Integration Data Architecture Information Engineering Data Governance Data Infrastructure Data Transformation DevOps Distributed Data Store Executive Information Systems
+11 more
Machine Learning Meta-Data Management Cloud Services DataOps Software Deployment Agentic-AI Data Strategy Enterprise Integration Data Management Machine Learning Operations Cloud Migration

Job description

We are seeking an accomplished and visionary Chief Data Officer to lead our enterprise-wide data strategy, cloud data modernization, governance, and AI-driven transformation initiatives. The ideal candidate will bring a strong blend of strategic leadership, technical expertise, and business acumen to build scalable, secure, and intelligent data ecosystems that drive measurable business outcomes across healthcare operations.

The Chief Data Officer will partner closely with C-suite executives and business leaders to establish a data-driven culture, modernize data platforms, strengthen data governance, and leverage advanced analytics, AI/ML, and agentic AI capabilities to improve clinical and operational efficiency, support value-based care, and enable better decision-making across payer, provider, and health-tech environments.

Key Responsibilities

  1. Enterprise Data Strategy & Leadership
  • Define and execute the enterprise-wide data strategy, roadmap, and operating model aligned with organizational objectives.
  • Lead and scale high-performing, globally distributed data engineering, architecture, analytics, and data science teams.
  • Manage P&L responsibilities, resource planning, budgets, and strategic investments across data initiatives. Establish enterprise data governance, data quality, metadata management, master data management, and data stewardship frameworks. *
  1. Healthcare Data & Regulatory Compliance

Drive data initiatives across healthcare ecosystems, including payer, provider, clinical operations, claims, and value-based care. Ensure compliance with HIPAA and HITECH regulations, healthcare data privacy, security, and applicable regulatory requirements. *

  1. Cloud Data Architecture & Modernization
  • Lead the design and implementation of scalable, secure, and high-performance cloud data platforms, including hands-on experience with Lakehouse architecture. Drive cloud modernization, data platform migration, and optimization initiatives across enterprise environments. *
  1. AI, Machine Learning & Agentic AI
  • Define and execute the AI/ML strategy, integrating advanced analytics and AI capabilities into healthcare and business workflows. Establish responsible AI practices covering model governance, explainability, monitoring, privacy, and risk management. *
  1. DevOps, DataOps & Operational Excellence

Drive DevOps, DataOps, MLOps, and CI/CD practices to accelerate the deployment and maintenance of data and AI solutions. *

  1. Business Value & Stakeholder Management
  • Align enterprise data initiatives with business priorities and measurable outcomes. Establish KPIs and executive dashboards to track data quality, platform performance, AI adoption, cost efficiency, and business value. *

Requirements

  • Extensive experience in enterprise data leadership, data strategy, data architecture, and large-scale digital transformation, preferably in a Chief Data Officer, VP of Data, Head of Data, or equivalent senior leadership role.
  • Mandatory healthcare industry experience across payer, provider, health-tech, healthcare services, or related healthcare data ecosystems.
  • Proven experience building and leading high-performing, globally distributed data and analytics organizations.
  • Strong expertise in cloud data platforms, Lakehouse architecture, data engineering, enterprise integration, and cloud modernization.
  • Demonstrated experience taking AI/ML solutions from strategy and experimentation through production deployment. Practical understanding of agentic AI, AI agents, reasoning models, and autonomous workflow orchestration. *, * Experience driving data transformation across large, complex, or multinational healthcare organizations.

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