Lead Data Solution Engineer

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 You'll design and deliver data integration solutions that support BI and AI work across Azure and on-prem environments. Your work will help turn complex data into reliable pipelines, useful reports, and data that can be used for machine learning and AI initiatives.

This role gives you the chance to work on several technically complex, business-critical projects at once. You'll be part of a team that values doing the right thing, building trusted relationships, and growing together.

You'll also join a fun and flexible environment with development support, hands-on learning, and work that has clear impact for the business and the people it serves.

How You'll Make An Impact You'll lead the design and delivery of scalable data pipelines that help bring BI and AI work to life across Azure and on-prem environments. You'll build reliable solutions that move data from source systems into clean, trusted structures that teams can use for reporting, analytics, and machine learning.

You'll also work hands-on with data ingestion, transformation, validation, and loading. That means pulling data from APIs, databases, Azure Blob Storage, ADLS Gen2, third-party systems, and on-prem SQL Server, then making sure it is accurate, available, and ready for use.

• Design and maintain ETL and ELT pipelines using Azure Data Factory, Azure Databricks, Synapse Analytics, and Azure SQL.
• Support on-prem SQL Server integration, including data extraction, synchronization, replication, and performance tuning.
• Write and optimize T-SQL queries, stored procedures, views, and functions to support processing, reporting, and analytics.
• Help maintain data quality, consistency, lineage, and governance through validation, reconciliation, and exception handling.
• Troubleshoot ETL failures, data latency issues, and production incidents across Azure and on-prem environments.
• Support data models, data marts, and feature stores for analytics and machine learning use cases.
• Develop, train, fine-tune, deploy, and monitor AI and ML models using structured and unstructured data.
• Apply Azure security practices, including RBAC, Managed Identities, Azure Key Vault, and private networking.
• Help improve ETL, ELT, and AI engineering processes through automation and modern Azure patterns.

About You

• You have 10+ years of experience in data solutions engineering, including 7+ years on the Microsoft platform.
• You have and Advanced English Level.
• You have 7+ years of experience designing and building large applications with SQL Server.
• You have worked with Azure Data Factory, Azure SQL, Azure Databricks, Synapse Analytics, Azure Functions, SQL Server, T-SQL, and SSIS.
• You have built or supported CI/CD pipelines and used DevOps tools to move code, database changes, and data through the release cycle.
• You have used Python and data libraries such as NumPy, Pandas, and PyArrow.
• You have built or supported AI and machine learning solutions in cloud environments, including work with vector databases.
• You can explain technical ideas clearly to managers, developers, vendors, and systems teams.
• You can lead a project team, shape a technology vision, and create detailed estimates for planned work.
• You have a bachelor’s degree in computer science, engineering, or a related field, or equivalent experience.