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.

Overview The Data Engineering Lead is a hands-on technical leader responsible for designing, building, and supporting the data platform that powers analytics, reporting, and AI  will lead complex data engineering initiatives while remaining deeply involved in the technology. This includes developing data pipelines, designing integrations, troubleshooting production issues, optimizing performance, reviewing code, and establishing engineering standards.

This is an individual contributor role with technical leadership responsibilities and no direct people management. You will work closely with data engineers, analytics, data science, business, and technology teams to translate business needs into scalable and reliable data solutions.

How you'll make an impact

Hands-On Data Engineering Design, develop, test, deploy, and support scalable ETL/ELT pipelines and data integrations.

Write production-quality SQL and Python/Scala/Spark code for data ingestion, transformation, and processing.

Build reusable, modular, and reliable data engineering frameworks and pipelines.

Work across Snowflake, Azure Data Factory, Databricks, Spark, ADLS Gen2, Azure Synapse, and SQL Server/Azure SQL.Develop curated datasets and data products supporting analytics, reporting, data science, and AI.Troubleshoot complex data, pipeline, integration, and performance issues.

Optimize pipelines, queries, compute, and storage for performance, reliability, and cost.

Technical Leadership Lead technical design and implementation of complex data engineering initiatives.

Translate business requirements into practical, scalable technical solutions.

Establish engineering standards for coding, testing, data quality, documentation, security, and deployment.

Conduct design and code reviews and establish reusable engineering patterns.

Mentor engineers and provide technical direction without direct management responsibility.

Identify technical risks, dependencies, and opportunities to simplify or modernize existing solutions.

Data Platform & Reliability Design scalable data lake, warehouse, and integration solutions using appropriate data modeling practices.

Build data quality, monitoring, logging, and observability into production pipelines.

Own the technical reliability of data pipelines and integrations.

Lead root-cause analysis and implement permanent fixes for production issues.

Improve CI/CD, release management, automation, and operational support practices.

Help reduce technical debt, manual processes, duplicate integrations, and single points of failure.

Business & AI Partnership Partner with business, analytics, data science, security, and technology teams to deliver data solutions aligned to business priorities.

Communicate technical decisions, risks, and tradeoffs clearly to technical and non-technical stakeholders.

Build data foundations that support AI and advanced analytics, including structured and unstructured data…