Data Engineering Manager

Introduction

Welcome to Gallagher - a global community of people who bring bold ideas, deep expertise, and a shared commitment to doing what’s right. We help clients navigate complexity with confidence by empowering businesses, communities, and individuals to thrive. At Gallagher, you’ll find more than a job; you’ll find a culture built on trust, driven by collaboration, and sustained by the belief that we’re better together.

Whether you join us in a client-facing role or as part of our brokerage division, our benefits and HR consulting division, or our corporate team, you’ll have the opportunity to grow your career, make an impact, and be part of something bigger. Experience a workplace where you’re encouraged to be yourself, supported to succeed, and inspired to keep learning. That’s what it means to live The Gallagher Way.

The Data Engineering Manager owns the design, delivery, and operation of the data platform that powers analytics, reporting, and AI  will lead and mentor data engineers, ensuring alignment with business goals and fostering collaboration across multiple teams, systems, and products. You will also oversee deliverables and provide ongoing support to ensure project success and operational excellence. This is a builder-manager role.

You will spend most of your time growing and directing the team, shaping the roadmap, and negotiating priorities with the business - while staying technical enough to review designs and code, unblock engineers, and manage multiple priorities.

Do you find the prospect of optimizing or even re-designing our company’s integration and data architecture to support our next generation of products and data initiatives most exciting? We really should explore together.

• Lead requirements gathering, scope definition, and technical design for data and integration workflows, providing strategic and architectural direction to the team.
• Set and enforce engineering standards - code review, ETL/ELT frameworks, testing, documentation, and definition of done.
• Proactively identify risks in data initiatives and develop mitigation strategies. Own the operational health of production data systems and integrations: SLAs, monitoring and alerting, incident response, and blameless post-incident review.
• Contribute to platform and tooling selection, capacity planning, vendor evaluation, and budget forecasting, including cloud and platform consumption costs.

• Hire, onboard, coach, and retain data engineers across onsite and offshore locations; own performance management, career development, and succession planning.
• Build a team operating model that scales - clear ownership, sustainable on-call and support rotation, and reduced single points of failure.
• Provide leadership, direction, and coordination for development and support teams across time zones, ensuring effective communication and collaboration.
• Partner with data science and analytics leaders to align engineering capacity with modeling, reporting, and AI priorities.

• Act as the liaison between technical teams and business users, ensuring data solutions meet real business needs and that concerns are addressed directly.
• Manage deliverables across multiple teams and products, ensuring timely completion and alignment with business priorities.
• Communicate platform health, delivery status, and roadmap changes transparently to both technical and non-technical audiences.

• Build and maintain the infrastructure required for optimal ETL/ELT pipelines, ingesting data from a wide variety of sources using cloud-native tooling such as Azure Data Factory, Databricks, and Snowflake.
• Construct and maintain…