Associate Director, Digital Measurement Platform & Systems Engineering

Job Overview

Develop fit for purpose platforms, systems, infrastructure, data pipelines, and AI/ML deployment capabilities to address digital measurement, healthcare, and innovative product applications. Design, build, test, deploy, and operate production-grade platforms, backend systems, automation frameworks, and deployment pipelines for product delivery. Test for viability in order to deliver reliable, scalable, and production-ready solutions. Able to bring newly developed technologies and engineering concepts into reality quickly and on a large scale.

Essential Functions

• Leads the transformation of platform, systems, infrastructure, and AI/ML engineering expertise into viable production-ready solutions.

• Provides technical leadership and mentorship to engineering teams while actively contributing to the development and delivery of platform, data, and AI/ML infrastructure capabilities.

• Leads the development of platform, backend, cloud, data, and deployment capabilities across products and engineering initiatives.

• Evaluates and drives adoption of new architectures, technologies, and engineering approaches in collaboration with software engineers, data engineers, machine learning engineers, and architects.

• Leads the building and deployment of new production-grade platforms, backend services, data pipelines, machine learning deployment frameworks, and automation systems that can process complex, high-dimensional data and support scalable analytics, AI/ML, and digital measurement applications.

• Uses a variety of techniques in order to improve the performance, scalability, reliability, and operational efficiency of platform, data processing, and machine learning production systems.

• Leads the testing and validation of platforms, systems, infrastructure, and deployment capabilities to determine viability for production deployment.

Qualifications

• Master's Degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, Artificial Intelligence, or related field

• 10+ years' experience designing, building, and operating production-grade software platforms, distributed systems, cloud infrastructure, data pipelines, and machine learning deployment environments

• Experience designing, building, and operating production-grade platforms, backend services, distributed systems, data pipelines, and cloud-native applications

• Programming experience using Python, Java, C++, or equivalent

• Experience with cloud-native platforms, Kubernetes, DevOps/MLOps practices, CI/CD pipelines, and Infrastructure as Code

• Experience deploying, scaling, and supporting machine learning, data processing, and analytics workloads in production environments

• Experience working with large-scale production systems, cloud environments, and real-world datasets

• Experience with release management, monitoring, observability, security, and operational best practices

• Proven experience leading engineering teams and driving delivery of complex platform, data, and cloud infrastructure initiatives

• Experience leading technical solution delivery and collaborating across engineering, data science, product, and architecture teams

IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com

IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism.