Lead Data Engineer

Magna Legal Services is a trusted nationwide partner to law firms, corporations, insurance carriers, and government agencies, delivering comprehensive legal support at every stage of a case.

Magna Legal Services is seeking a hands-on Lead Data Engineer to provide technical leadership for the design, development, and ongoing evolution of our enterprise data platform. This role will own the architecture and optimization of scalable ETL/ELT pipelines and our Snowflake data warehouse, establish engineering standards, and guide the delivery of reliable data solutions across the organization. The Lead Data Engineer will partner with technical and business stakeholders, mentor team members, and remain actively involved in implementation as we modernize and scale our data infrastructure.

Primary Responsibilities

• 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.