US Health Analytics Data Engineering Team Leader

About the role

Aon is seeking a Health Analytics Data Engineering Leader to lead a distributed data engineering team supporting US Health Analytics solutions. This role is responsible for translating business needs into scalable, cloud-first data solutions and leading a distributed team to deliver high-quality solutions with speed, clarity, and strong engineering discipline.

Responsibilities

• Owns the end-to-end medallion US Health Analytics data architecture and is accountable for scaled structured data flows and data partner integrations, enrichments, and downstream processing across each stage.
• Supports analytics-ready data capabilities consumed by consultants, actuaries, analytics applications, and AI agents, ensuring each layer is well-governed, performant, and fit for purpose.
• Owes the quality, monitoring, validation, completeness, and reliability of data across the platform, and owns the design and operation of scaled, multi-way data pipelines with key partners - ingesting external and partner data into the platform and delivering trusted, enriched data back out to stakeholders following strict governance, privacy, HIPAA, SOC, contractual, and cybersecurity standards.
• Serves as senior engineering leader and also leads through influence and collaboration as part of a globally distributed team. Partners closely with Aon Business Services and Aon Data & Analytics engineering teams, architects, and infrastructure teams to ensure Aon enterprise standards and best practices are adopted and followed for Health Analytics data.

Requirements

• Team management experience in a global enterprise environment. Manages data engineers and coordinates activity across a globally distributed team spanning several departments working closely with Aon Business Solutions and global Data & Analytics organization.
• 10+ years of relevant experience in data engineering, software engineering, analytics engineering, or related technical leadership roles.
• Experience with Medallion architecture and operations in domain-relevant environment. Deep experience designing and delivering cloud-first data engineering solutions using Apache Spark, Databricks, Python, Git, Azure DevOps, CLI tools, and related platforms.
• Strong general software engineering capability, including clean code, modular design, reusable interfaces, automated testing, CI/CD, DevOps practices, and maintainable production systems.
• Demonstrated expertise in data modeling, data architecture, and scalable platform design, with the ability to make practical decisions that balance future-state architecture with timely delivery.
• Knowledge of HIPAA, data privacy, data security, access controls, de-identification, and related practices for sensitive health data.
• Experience leading distributed teams, setting priorities, coaching technical colleagues, and building a high-performing engineering culture.
• Ability to translate business needs into technical roadmaps, execution plans, and scalable data capabilities that improve speed, quality, and operating leverage.
• Experience with agentic AI, AI-enabled automation, or emerging engineering workflows that improve productivity, data quality, or analytics delivery.
• Practical data governance experience such as privilege management and monitoring, cataloging, retention policies, and data sharing.
• Capable of writing production software, but skilled at leveraging teams to deliver beyond individual effort.

Qualifications

• Bachelor’s or master’s degree in computer science, data engineering, health informatics, information technology, actuarial science, mathematics, statistics, or a related field, or equivalent professional experience.

Skills

• Advanced Analytics
• Data Analysis
• Data Integration
• Data Management
• Data Mining
• Data Modeling
• Data Science
• Data Visualization
• Predictive Modeling
• Python Programming
• Statistical Analysis