Data Engineering Lead
arthur j gallagherRolling Meadows, IL
About the role
Overview:
In this role you will lead the design, delivery, and operation of Gallagher’s data platform to enable analytics, reporting, and AI. You’ll mentor a cross-functional data engineering team, align work with business goals, and shape the data & integration roadmap. You’ll manage production reliability, cost, and collaboration across time zones, balancing hands-on review with people leadership. This is a builder-manager role focused on scalable data foundations and AI-enabled capabilities that impact decision making and product outcomes. You’ll work in a collaborative, cross-functional environment to drive measurable data-driven impact across the organization. Compensation / Benefits Competitive compensation Comprehensive benefits programs Career development and ongoing learning Collaborative, people-first culture Global reach with local impact Supportive leadership and employee well-being
Responsibilities:
Provide architectural direction and oversee requirements gathering, scope definition, and technical design for data and integration workflows Set and enforce engineering standards including code reviews, ETL/ELT frameworks, testing, and documentation Manage operational health of production data systems: SLAs, monitoring, incident response, and post-incident reviews Lead platform and tooling decisions including capacity planning, vendor evaluation, and cloud cost management Hire, onboard, coach, and retain data engineers across locations; manage performance and career development Coordinate across time zones to ensure effective communication and collaboration between development and support teams Partner with data science and analytics leaders to align engineering capacity with AI/BI priorities Act as liaison between technical teams and business users to ensure data solutions meet business needs Build and maintain ETL/ELT pipelines and data integrations using cloud-native tools (Azure Data Factory, Databricks, Snowflake) Own data modeling standards and semantic layer for analytics/BI consumption Implement data quality, observability, lineage, and cataloging practices Drive process improvements, automation, and scalable infrastructure to reduce manual work and cost Design and operate data foundations for AI including feature pipelines and training datasets Evaluate and integrate AI capabilities and establish governance around AI use of enterprise data
Key requirements:
Bachelor in Information Technology 5+ years leading a technical team 7+ years data engineering experience with Snowflake, Azure Data Factory, ADLS Gen 2, Azure Functions, Databricks, Synapse, SQL Server Experience delivering data foundations for AI/ML workloads (feature pipelines, training datasets, embeddings, model deployment support) Governance of AI use of sensitive data (access, masking, lineage, auditability) Experience with Data Lake architectures on Microsoft Azure Experience ETL for Data Warehouse and BI solutions Strong coding skills with modular, robust, parameterized ETL/ELT code and adherence to standards Knowledge of DevOps, CI/CD, and Infrastructure as Code Experience in agile environments and root cause analysis for data processes Excellent communication and stakeholder management across levels Ability to navigate ambiguity and deliver for multiple teams and priorities Proven track record of delivering on data systems and integrations across projects Strong communication and interpersonal skills Collaboration and stakeholder management Leadership and mentoring Snowflake Azure Data Factory ADLS Gen 2
Matching similar jobs
JOB OVERVIEW
Experience level
Manager
Location
Rolling Meadows, IL
Occupation
Data Warehousing Specialists
Industry
Computer Systems Design Services
Posted
today
Tired of running searches?
Rank the roles you'd take once, and matches like these arrive on their own.
CREATE PROFILE (opens in a new tab)