magnals - Magna Legal Services - Lead Data Engineer

• Own the technical direction, architecture, and ongoing evolution of our Snowflake data warehouse, with accountability for performance, scalability, security, reliability, and cost efficiency. • Lead the design, development, and standardization of scalable ETL/ELT pipelines across data sources and destinations, including the continued evolution toward Azure Data Factory. • Establish and uphold engineering standards for code quality, testing, documentation, version control, deployment, monitoring, and data quality. • Lead the design and development of dimensional data models, including star schemas within a medallion architecture, using tools such as dbt, Sigma, and related technologies. • Partner with technical and business stakeholders to translate data needs into a prioritized technical roadmap and deliver trusted, reusable data solutions that support decision-making across the company. • Provide technical guidance through solution design and code reviews, mentor data engineers and analysts, and help the team resolve complex technical challenges. • Evaluate and introduce tools, patterns, and process improvements that strengthen scalability, reliability, maintainability, and delivery efficiency. • Lead complex and ad hoc data engineering initiatives from requirements through delivery while promoting data governance, data literacy, and responsible data practices across the organization. • ## Desired Background • Bachelor's degree in computer science, Information Technology, Engineering, or a related field. • 5+ years of progressive experience in data engineering, including ownership of complex initiatives and technical leadership within a modern cloud data environment. • Advanced hands-on experience with Snowflake, including data warehouse architecture, performance tuning, security and access controls, and cost optimization. • Advanced SQL skills and strong experience with a scripting language such as Python for data processing, automation, and troubleshooting. • Strong experience designing and operating scalable ETL/ELT pipelines, including orchestration, testing, monitoring, and production support. • Hands-on experience with dimensional data modeling, star schema and medallion architectures, and dbt or a comparable transformation framework. • Experience with Azure Data Factory or a comparable cloud orchestration platform; experience modernizing or migrating legacy data pipelines is preferred. • Demonstrated technical leadership through mentoring, design and code reviews, engineering standards, and cross-functional delivery, with strong communication and prioritization skills.