数据工程人工智能总监

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, 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

Cognitive/Mental Requirements

• Problem-solving and thinking critically.

• Completing tasks independently.

• Interpreting data.

• Maintaining focus.

Physical Requirements and Working Conditions:

• Remaining in a stationary position, often standing or sitting for prolonged periods.

• Repeating motions that may include the wrists, hands and/or fingers.

• Must be able to provide a dedicated, secure work area.

• Must be able to provide high-speed internet access / connectivity and office setup and maintenance.

Base compensation ranges from $190,000 to $225,000 per year. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs. This role is eligible for discretionary bonus consideration.
Cotiviti offers team members a competitive benefits package to address a wide range of personal and family needs, including medical, dental, vision, disability, and life insurance coverage, 401(k) savings plans, paid family leave, 9 paid holidays per year, and 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti. For information about our benefits package, please refer to our Careers page.
Since this job will be based remotely, all interviews will be conducted virtually.
Date of posting: 6/08/2026
Applications are assessed on a rolling basis. We anticipate that the application window will close on 09/08/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.
Originally posted on Himalayas