Senior Data Engineer - Snowflake & ETL Architect

Magnals

United States

Remote

USD 140,000 - 190,000

Full time

14 days+

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Job summary

Magna Legal Services is seeking a hands-on Lead Data Engineer to provide technical leadership for the design, development, and evolution of our enterprise data platform. This role will own the architecture and optimization of scalable ETL/ELT pipelines and our Snowflake data warehouse, establishing engineering standards and guiding reliable data solutions.

The Lead Data Engineer will mentor team members, partner with stakeholders, and drive modernization and scalability across the data

Qualifications

BS/BA in computer science, information technology, engineering, or related field.
5+ years in data engineering with leadership experience in modern cloud data environments.
Advanced Snowflake experience: data warehouse architecture, performance tuning, security, cost optimization.
Advanced SQL + Python for data processing, automation, troubleshooting.
Experience designing scalable ETL/ELT pipelines with orchestration, monitoring, production support.
Dimensional data modeling including star schemas and medallion architecture; dbt or equivalent.
Experience with Azure Data Factory or similar cloud orchestration; migration of legacy pipelines.
Strong leadership: mentoring, design reviews, engineering standards, cross-functional delivery, prioritization.

Responsibilities

Own Snowflake data warehouse architecture, performance, security, reliability, and cost efficiency.
Lead design and standardization of scalable ETL/ELT pipelines across sources and destinations.
Establish and uphold engineering standards for code, tests, docs, version control, deployment, monitoring, and data quality.
Design and develop dimensional models (star schemas) within medallion architecture using dbt, Sigma, and related tools.
Translate data needs into a prioritized technical roadmap and deliver reusable data solutions for decision making.
Provide technical guidance via solution design, reviews, and mentoring data engineers and analysts.
Evaluate tools and processes to improve scalability, reliability, maintainability and delivery velocity.
Lead complex data engineering initiatives from requirements to delivery while advocating data governance.