US Health Analytics Data Engineering Team Leader

Aon Corporation•Atlanta, GA

4d•Hybrid

About The Position

Aon is looking for a Health Analytics Data Engineering Leader to lead a distributed data engineering team supporting US Health Analytics solutions. This experienced team leader 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. This leader 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. The team 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. The leader is accountable for 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. This role serves as senior engineering leader and also leads though influence and collaboration as part of a globally distributed team. The leader will partner 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.
Manage data engineers and coordinate 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 a 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.
Experience with US commercial healthcare data, including plan designs, premiums & contributions, ASO fees, medical & pharmacy claims, eligibility, enrollment, and related benefits data used by consultants and actuaries.
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.
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.

Responsibilities

Translate business needs into scalable, cloud-first data solutions.
Lead a distributed team to deliver high-quality solutions with speed, clarity, and strong engineering discipline.
Own the end-to-end medallion US Health Analytics data architecture.
Ensure scaled structured data flows and data partner integrations, enrichments, and downstream processing.
Support analytics-ready data capabilities consumed by consultants, actuaries, analytics applications, and AI agents.
Ensure each data layer is well-governed, performant, and fit for purpose.
Accountable for the quality, monitoring, validation, completeness, and reliability of data across the platform.
Own the design and operation of scaled, multi-way data pipelines with key partners.
Ingest external and partner data into the platform.
Deliver trusted, enriched data back out to stakeholders following strict governance, privacy, HIPAA, SOC, contractual, and cybersecurity standards.
Partner closely with Aon Business Services and Aon Data & Analytics engineering teams, architects, and infrastructure teams.
Ensure Aon enterprise standards and best practices are adopted and followed for Health Analytics data.
Drive results by creating clarity, establishing priorities, and leading the team to deliver measurable outcomes with speed, accountability, and quality.
Think strategically and practically by understanding business needs, designing for the future, and making pragmatic decisions that keep work moving forward.
Lead and develop colleagues by building an inclusive, high-performing team environment and developing technical talent across geographies and experience levels.
Collaborate effectively across actuarial, consulting, data science, technology, and business teams.
Champion innovation and continuous improvement by moving teams toward modern methods, automation, AI-enabled workflows, and scalable ways of working.
Write production software and leverage teams to deliver beyond individual effort.