Lead Data Engineer needed to design, build, and manage data pipelines (data ingestion, transformation, distribution, quality rules, data storage) and AI-powered solutions within Inspire Brands' Enterprise Data Organization. The role requires strong technical, analytical, programming, and critical-thinking skills. Responsibilities include leading multiple data engineering team members, designing, building, deploying and documenting AI solutions from concept to operations, implementing infrastructure as code, automated testing, and modern observability strategies; mentoring and fostering an engineering culture through leadership and presentations across data teams. Collaborate with product owners/managers, architects, data modelers, and other team members to design data and AI jobs that meet business needs; lead sessions with data engineers to solve technical challenges; develop or enhance data processes (ingest, transform, store, data management, data quality); contribute to data engineering best practices and ensure production-ready, scalable code; document technical artifacts; stay current with AI trends and integrate emerging technologies to improve system performance with balanced pragmatism. Education and experience: 8+ years in data engineering; 5+ years with advanced SQL queries, scripts, stored procedures, materialized views, and views; 5+ years for ELT data loading and transformations in databases; 3+ years using CI/CD and DevOps models; experience with Azure, AWS, or GCP (Azure preferred); Python proficiency; Snowflake experience a plus; strong analytical SQL skill

Lead Data Engineer needed to design, build, and manage data pipelines (data ingestion, transformation, distribution, quality rules, data storage) and AI-powered solutions within Inspire Brands' Enterprise Data Organization. The role requires strong technical, analytical, programming, and critical-thinking skills. Responsibilities include leading multiple data engineering team members, designing, building, deploying and documenting AI solutions from concept to operations, implementing infrastructure as code, automated testing, and modern observability strategies; mentoring and fostering an engineering culture through leadership and presentations across data teams. Collaborate with product owners/managers, architects, data modelers, and other team members to design data and AI jobs that meet business needs; lead sessions with data engineers to solve technical challenges; develop or enhance data processes (ingest, transform, store, data management, data quality); contribute to data engineering best practices and ensure production-ready, scalable code; document technical artifacts; stay current with AI trends and integrate emerging technologies to improve system performance with balanced pragmatism. Education and experience: 8+ years in data engineering; 5+ years with advanced SQL queries, scripts, stored procedures, materialized views, and views; 5+ years for ELT data loading and transformations in databases; 3+ years using CI/CD and DevOps models; experience with Azure, AWS, or GCP (Azure preferred); Python proficiency; Snowflake experience a plus; strong analytical SQL skill