US Health Analytics Data Engineering Team Leader

Aon is looking for 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
• 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
• Accountable for the quality, monitoring, validation, completeness, and reliability of data across the platform
• 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
• Partners closely with Aon Business Services and Aon Data & Analytics engineering teams, architects and infrastructure teams ensuring Aon enterprise standards and best practices are adopted and followed for Health Analytics data

Requirements:

• Team management experience in a global enterprise environment
• 10+ years of relevant experience in data engineering, software engineering, analytics engineering, or related technical leadership roles
• 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
• Experience with US commercial healthcare data, including plan designs, premiums & contributions, ASO fees, medical & pharmacy claims, eligibility, enrollment and related benefits data
• 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
• Experience with agentic AI, AI-enabled automation, or emerging engineering workflows
• 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
• Advanced Analytics, Structured Query Language (SQL), Data Analysis, Data Integration, Data Management, Data Mining, Data Modeling, Data Science, Data Visualization, Predictive Modeling, Project Management, Python Programming, and Statistical Analysis
• 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