Lead Data Solution and AI Engineer

Introduction At Gallagher Bassett, we're there when it matters most because helping people through challenging moments is more than just our job, it’s our purpose. Every day, we help clients navigate complexity, support recovery, and deliver outcomes that make a real difference in people’s lives. It takes empathy, precision, and a strong sense of partnership—and that’s exactly what you’ll find here.

We’re a team of fast-paced fixers, empathetic experts, and outcomes drivers — people who care deeply about doing the right thing and doing it well. Whether you're managing claims, supporting clients, or improving processes, you’ll play a vital role in helping businesses and individuals move forward with confidence. Here, you’ll be supported by a culture that values teamwork, encourages curiosity, and celebrates the impact of your work.

Because when you’re here, you’re part of something bigger. You’re part of a team that shows up, stands together, and leads with purpose. How you'll make an impact

The Lead Data Solution and AI Engineer developer provides guidance, leadership, and solid execution of data integration solutions as they related to BI and AI project initiatives. Typically, this role participates in multiple, technically complex, mission-critical, and/or high-profile data projects or initiatives. This individual must possess strong leadership skills including the ability to make sound data architectural solutions recommendations.

Key Responsibilities:

Data Platform and Pipeline Delivery Design and maintain scalable ETL/ELT pipelines using Azure Data Factory, Azure Databricks, Synapse Analytics, and Azure SQL to support analytics, reporting, and AI/ML workloads.

Develop data ingestion, transformation, validation, and loading workflows from APIs, databases, Azure Blob Storage, ADLS Gen2, third-party systems, and on-premises SQL databases.

Support on-premises SQL Server integration, including data extraction, synchronization, replication, and performance tuning.

Write and optimize T-SQL queries, stored procedures, views, and functions to support data processing, reporting, and analytics.

Support data models, data marts, and feature stores for analytics and machine learning use cases.

Develop, train, fine-tune, deploy, and monitor AI/ML models using structured and unstructured data, including model versioning, performance tracking, and retraining.

Develop AI-powered capabilities using modern large language models (LLMs) and AI services.

Implement intelligent search, knowledge retrieval, and automation solutions.

Troubleshoot ETL failures, data latency issues, and production incidents across Azure and on-premises environments.

Process Improvement and Operational Excellence Identify and implement process improvements that automate manual activities and improve data delivery.

Improve the performance, scalability, reliability, and maintainability of data engineering solutions.

Security, Governance and Compliance Apply Azure security best practices, including RBAC, Managed Identities, Azure Key Vault, and private networking.

Ensure data quality, consistency, lineage, and governance through validation, reconciliation, and exception-handling processes.

People Leadership Provide technical guidance and leadership to junior developers.

Provide data architecture recommendations, project team leadership, technology vision, and detailed estimates.

Core technical stack:

Data Platform and Engineering Microsoft/Azure:
Azure Data Warehouse, Azure SQL Database / Synapse, Azure Data Factory, Azure Functions, SQL Server, T-SQL, SSISData & engineering tools:
Dev Ops, Databricks AI and Advanced Analytics Enablement Python, Num Py, Pandas, PyArrowAI/LLM tools:
OpenAI, Lang Chain, Llama Index, AI tools, Vector Database…