Director, Data Engineering – Artificial Intelligence

This is a fully remote position, open to applicants in United States.

📋 Description

• Supervise data engineering initiatives to ensure Cotiviti can deliver scalable and reliable data pipelines from various backend data sources to the cloud platform, utilizing top-tier cloud-native technologies (AWS, Azure, or GCP) and contemporary frameworks such as Spark, Kafka, dbt, Databricks, and the Cloudera/Hadoop ecosystem.

• Lead and manage a team of data engineers to produce high-quality code and develop data products and use cases, promoting a culture of engineering excellence, accountability, and continuous improvement across multiple functional squads.

• Ensure adherence to best practices in data architecture and engineering standards, establishing pipelines with reusable, scalable engineering patterns that align with data mesh principles and enterprise platform engineering.

• Shape the vision for the data engineering platform by creating data products that support various use cases and projects — including AI/ML applications, Analytics and BI initiatives, and LLM-powered Agentic use cases — collaborating closely with Architecture and Product Management teams to define the data product roadmap.

• Implement a metrics- and KPIs-driven strategy to evaluate the data engineering team's output, assess the business value of created data products, and continuously monitor and enhance team performance and throughput.

• Influence the architecture of AI/ML and Agentic AI solutions, partnering with Data Science, Product, and business line teams to ensure the data infrastructure is equipped for AI, including feature store availability, embedding pipelines, vector databases, and real-time serving capabilities.

• Conceptualize and spearhead Proof of Concepts and MVPs that strengthen Cotiviti's data engineering capabilities amidst the rapidly evolving landscape of AI, generative AI, and agentic systems.

• Identify and evaluate key business risks associated with meeting the data needs of the organization, proactively communicating risks and mitigation strategies to VP- and C-suite stakeholders.

• Promote robust data engineering practices throughout the organization by articulating the vision and use cases for advanced analytics, data products, and AI-enabled capabilities to both technical and non-technical audiences.

• Recruit, develop, coach, lead, and retain top-tier talent, focusing on building and enhancing a team and culture that employs best-in-class practices to achieve high levels of internal and external customer satisfaction.

• Fulfill all responsibilities detailed in the annual performance review and/or goal setting, and complete special projects and other assigned duties.

⛳️ Requirements

• Bachelor’s degree with 12+ years of professional experience in a data engineering, analytical, or information specialist role within a corporate or consulting environment; experience in healthcare, life sciences, or a related field is highly preferred.

• In-depth 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, along with the Cloudera/Hadoop ecosystem.

• Strong foundational knowledge and perspective on generative AI techniques like LLMs and Agentic architectures for addressing data engineering challenges.

• Proven track record in designing and implementing enterprise data architectures on cloud platforms, with hands-on expertise in ETL/ELT, data modeling, data integration, and the modern data stack (Spark, dbt, Kafka, Airflow).

• Comprehensive understanding of data governance, data quality, and data security best practices, including HIPAA compliance and the responsible handling of sensitive healthcare and claims data.

• Clear expertise in generative AI techniques — including LLMs and Agentic architectures — and their application in solving data engineering challenges at an enterprise level.

• Demonstrated capability to tackle complex business challenges by developing scalable data products that reveal insights from both structured and unstructured data, including the ability to create examples, prototypes, and demonstrations that enhance leadership’s comprehension of the work.

• Proven experience in leading and managing large data engineering teams (15+ Data Engineers), focusing on hiring, developing, coaching, and retaining top-tier talent with an emphasis on high performance and customer satisfaction.

• Proficient at planning and establishing meaningful objectives that align with organizational goals; ability to articulate, advocate for, and implement strategic plans while managing multiple concurrent projects, shifting priorities, and strict deadlines.

• Outstanding written, verbal, and interpersonal communication skills, with the ability to identify and communicate business challenges, project objectives, and engineering strategies to both technical and non-technical audiences, including executive stakeholders.

• Strong initiative, self-motivation, and the ability to work independently while also leading and collaborating within large cross-functional teams in a customer-focused environment.

🏝️ Benefits

• Medical, dental, vision, disability, and life insurance coverage.

• 401(k) savings plans.

• Paid family leave.

• 9 paid holidays per year.

• 17-27 days of Paid Time Off (PTO) per year, based on specific level and length of service with Cotiviti.