Director Data Engineering Artificial Intelligence

## Overview We are seeking a seasoned Director of Data Engineering to lead and scale a high-performing, enterprise-grade data engineering organization for a healthcare company with petabytes of data. This role is responsible for architecting and governing the data infrastructure and drive the technical roadmap across foundational infrastructure, streaming pipelines, analytics engineering, and AI enablement, and serve as a strategic partner to product, analytics, clinical informatics, and technology leadership ## 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. - Complete all special projects and other duties as assigned. - Must be able to perform duties with or without reasonable accommodation. This job description is intended to describe the general nature and level of work being performed and is not to be construed as an exhaustive list of responsibilities, duties and skills required. This job description does not constitute an employment agreement and is subject to change as the needs of Cotiviti and requirements of the job change. ## Qualifications - **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, technolog…