Director Data Engineering Artificial Intelligence

Cotiviti is a healthcare company seeking a seasoned Director of Data Engineering to lead and scale their data engineering organization. This role involves architecting and governing the data infrastructure, managing a team of data engineers, and driving the technical roadmap for AI enablement and analytics engineering.

Responsibilities:

• Oversee the data engineering efforts in ensuring that Cotiviti is able to provision scalable, reliable data pipelines from the various backend data sources to the cloud platform, applying best-in-class cloud-native technologies (AWS, Azure, or GCP) and modern frameworks including Spark, Kafka, dbt, Databricks, and the Cloudera/Hadoop ecosystem
• Lead and manage a team of data engineers in delivering quality code and building data products and use cases, fostering a culture of engineering excellence, accountability, and continuous improvement across multiple functional squads
• Ensure the organization follows best practices in data architecture and engineering standards so that pipelines are established with reusable, scalable engineering patterns aligned to data mesh principles and enterprise platform engineering
• Influence the vision for the data engineering platform in creating data products that power multiple use cases and projects — including AI/ML use cases, Analytics and BI use cases, and LLM-powered Agentic use cases — collaborating closely with Architecture and Product Management teams to shape the data product roadmap
• Establish a metrics- and KPIs-driven approach to measure the work done by the data engineering team, track business value of data products created, and monitor, measure, and continuously improve team performance and throughput
• Influence solution architecture of AI/ML and Agentic AI solutions, collaborating with Data Science, Product, and line-of-business teams to ensure data infrastructure is AI-ready, including feature store availability, embedding pipelines, vector databases, and real-time serving capabilities
• Ideate and lead Proof of Concepts and MVPs that advance Cotiviti's data engineering posture in the rapidly evolving landscape of AI, generative AI, and agentic systems
• Identify and monitor key business risks related to realizing the data needs of the business, communicating risks and mitigation strategies proactively to VP- and C-suite stakeholders
• Evangelize strong data engineering patterns and practices throughout the organization by communicating the vision and use cases of advanced analytics, data products, and AI-enabled capabilities to both technical and non-technical audiences
• Hire, develop, coach, lead, and retain top-tier talent, with a focus on building and improving a team and culture that employs best-in-class practices to drive high levels of internal and external customer satisfaction
• Complete all responsibilities as outlined in the annual performance review and/or goal setting. Required
• Complete all special projects and other duties as assigned. Required
• Must be able to perform duties with or without reasonable accommodation. Required

Requirements:

• Bachelor's degree and 12+ of professional experience required in a data engineering, analytical, or information specialist role within a corporate or consulting setting; experience in healthcare, life sciences, or a related industry strongly preferred
• Deep understanding of data engineering architectures, technologies, and platforms focused on large-scale data management and AI applications, including cloud-native platforms such as Databricks, GCP, and AWS, as well as the Cloudera/Hadoop ecosystem
• Strong foundation and point of view on generative AI techniques like LLMs and Agentic architectures in solving data engineering problems
• Proven expertise in designing and implementing enterprise data architectures on cloud platforms, with hands-on fluency in ETL/ELT, data modeling, data integration, and the modern data stack (Spark, dbt, Kafka, Airflow)
• Deep understanding of data governance, data quality, and data security best practices, including HIPAA compliance and handling of sensitive healthcare and claims data in a discretionary manner
• Strong foundation and clear point of view on generative AI techniques — including LLMs and Agentic architectures — and how they apply to solving data engineering problems at enterprise scale
• Demonstrated ability to solve complex business problems by creating scalable data products that surface insights from both structured and unstructured data, including the ability to create examples, prototypes, and demonstrations that help leadership better understand the work
• Proven ability to lead and manage large data engineering teams (15+ Data engineers), including hiring, developing, coaching, and retaining top-tier talent with a focus on high performance and customer satisfaction
• Proficiency at planning and setting meaningful objectives aligned to organizational goals; ability to articulate, promote, and implement strategic plans while managing multiple concurrent projects, shifting priorities, and firm deadlines
• Exceptional written, verbal, and interpersonal communication skills with the ability to identify and articulate business challenges, project objectives, and engineering approaches to both technical and non-technical audiences, including executive stakeholders
• Strong initiative, self-motivation, and ability to work autonomously while also leading and collaborating within large cross-functional teams in a customer-service-oriented environment
• Oversee the data engineering efforts in ensuring that Cotiviti is able to provision scalable, reliable data pipelines from the various backend data sources to the cloud platform, applying best-in-class cloud-native technologies (AWS, Azure, or GCP) and modern frameworks including Spark, Kafka, dbt, Databricks, and the Cloudera/Hadoop ecosystem
• Lead and manage a team of data engineers in delivering quality code and building data products and use cases, fostering a culture of engineering excellence, accountability, and continuous improvement across multiple functional squads
• Ensure the organization follows best practices in data architecture and engineering standards so that pipelines are established with reusable, scalable engineering patterns aligned to data mesh principles and enterprise platform engineering
• Influence the vision for the data engineering platform in creating data products that power multiple use cases and projects — including AI/ML use cases, Analytics and BI use cases, and LLM-powered Agentic use cases — collaborating closely with Architecture and Product Management teams to shape the data product roadmap
• Establish a metrics- and KPIs-driven approach to measure the work done by the data engineering team, track business value of data products created, and monitor, measure, and continuously improve team performance and throughput
• Influence solution architecture of AI/ML and Agentic AI solutions, collaborating with Data Science, Product, and line-of-business teams to ensure data infrastructure is AI-ready, including feature store availability, embedding pipelines, vector databases, and real-time serving capabilities
• Ideate and lead Proof of Concepts and MVPs that advance Cotiviti's data engineering posture in the rapidly evolving landscape of AI, generative AI, and agentic systems
• Identify and monitor key business risks related to realizing the data needs of the business, communicating risks and mitigation strategies proactively to VP- and C-suite stakeholders
• Evangelize strong data engineering patterns and practices throughout the organization by communicating the vision and use cases of advanced analytics, data products, and AI-enabled capabilities to both technical and non-technical audiences
• Hire, develop, coach, lead, and retain top-tier talent, with a focus on building and improving a team and culture that employs best-in-class practices to drive high levels of internal and external customer satisfaction
• Complete all responsibilities as outlined in the annual performance review and/or goal setting
• Complete all special projects and other duties as assigned
• Must be able to perform duties with or without reasonable accommodation
• Experience in healthcare, life sciences, or a related industry strongly preferred