Data Architect - Insurance Data

Data ArchitectThe Data Architect is a hands-on technical leader responsible for designing the data architecture, models, standards, and patterns that enable scalable, trusted, and reusable enterprise data solutions at Gallagher. You will lead the architecture and design of complex data initiatives spanning operational, analytical, master, and reference data. This includes defining end-to-end data flows, developing conceptual and logical data models, establishing integration and modeling patterns, evaluating solution designs, and ensuring data platforms are designed for scalability, reliability, governance, security, and long-term maintainability.This is an individual contributor role with technical leadership responsibilities and no direct people management. You will work closely with data engineers, solution and enterprise architects, product teams, analytics, data science, governance, business stakeholders, and technology teams to translate business capabilities and data requirements into practical enterprise data architectures.Required: Typically requires a University Degree and minimum 3 years of prior relevant experience, or equivalent experience. Our ideal candidate will have a Bachelor's degree in Computer Science, Information Technology, Engineering, Data Management, or related field. 7+ years of experience working with enterprise data platforms, data engineering, data modeling, or data architecture, including significant experience in a data architecture or senior technical design role. Proven experience designing enterprise data architectures across complex data ecosystems. Strong experience with conceptual and logical data modeling, including defining business entities, relationships, domains, and canonical models. Strong understanding of data lake, data warehouse, lakehouse, data integration, master data, and modern data platform concepts. Experience designing solutions on modern cloud data platforms such as Snowflake, Azure, Databricks, ADLS Gen2, Azure Data Factory, and SQL-based platforms. Strong understanding of ETL/ELT, APIs, event-driven integration, and other enterprise data integration patterns. Experience establishing data architecture, modeling, integration, and documentation standards. Strong understanding of data governance, metadata, lineage, data quality, security, and data ownership concepts. Ability to translate complex business requirements into clear data architectures and technical designs. Ability to lead architecture initiatives and influence engineering and technology teams without direct management authority. Strong analytical, problem-solving, communication, and stakeholder-management skills.