AI Native Data Engineer

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field (or equivalent professional experience) 3-5 years of professional data engineering experience Strong SQL and relational database experience (SQL Server/Azure SQL preferred) Experience with ETL/ELT pipeline development and maintenance Experience with data warehouse design patterns and data modeling fundamentals Experience building and maintaining data warehouse objects including tables, views, and stored procedures Ability to work within AI-assisted development environments utilizing GitHub Copilot and Claude Experience using Git-based source control and Jira workflow Experience with Microsoft Fabric Experience with Azure SQL and SQL Server environments Experience in Agile/Scrum environments Experience working with distributed onshore/offshore teams Strong understanding of automated testing and data quality validation practices

Insight Global is seeking a Data Engineer, AI-Native for a leading legal technology and healthcare services organization. This candidate will join a growing data engineering team focused on building scalable data solutions that power innovative business operations and customer-facing platforms. The ideal candidate will have strong experience developing ETL/ELT pipelines, working with SQL-based data platforms, and supporting modern data warehouse environments. This role offers the opportunity to work in a highly innovative AI-native development environment, leveraging tools such as GitHub Copilot and Claude while partnering closely with cross-functional teams to deliver impactful data solutions. The position is ideal for a hands-on data engineer who enjoys owning projects end-to-end and contributing to the future of AI-assisted software development.

Gather, document, and validate business and technical requirements using AI-assisted workflows Design, build, and maintain ETL/ELT pipelines and data warehouse solutions Develop and support tables, views, stored procedures, and transformations across Microsoft Fabric, Azure SQL, and SQL Server environments Own data engineering projects from design through deployment and production support Create and maintain data quality checks, automated testing, and validation processes Participate in code reviews and technical planning sessions Collaborate with cross-functional stakeholders and engineering teams in Agile ceremonies Utilize AI tools such as GitHub Copilot, Claude, and Claude Code to accelerate development while validating all generated output Work within an AI-native engineering model alongside AI agents throughout the SDLC