Data Engineer

Role overview Develop and operate a cloud data warehouse and the pipelines that support analytics, business intelligence, and machine learning. You’ll turn requirements from business and technical partners into dependable, documented data models, while improving data quality, observability, performance, and cost efficiency. The role emphasizes production experience with Snowflake and modern ELT development practices.

Responsibilities - Build and maintain scalable ELT or ETL pipelines and supporting data infrastructure in a Snowflake environment. - Develop data models using dimensional, data vault, or medallion and lakehouse approaches to serve different analytical needs. - Collaborate with analytics, product, and engineering partners to shape and document technical solutions. - Establish automated data checks and observability practices to improve pipeline reliability. - Contribute to governance through documentation, lineage, access controls, and compliance practices. - Monitor and improve warehouse performance, compute spending, and data freshness. - Evaluate platform features and tooling, and use AI-assisted development tools to speed up implementation, review, and documentation.

Requirements - At least five years of data engineering experience building production pipelines and working with distributed computing. - At least three years using Snowflake in production, including warehouse configuration, access controls, performance, and cost optimization. - Experience with modern ELT tools such as dbt, Fivetran, Airflow, or Prefect. - Advanced SQL skills and proficiency in a programming language; Python is preferred. - Experience contributing to a Snowflake warehouse migration or rebuild. - Familiarity with version control and CI/CD for data pipelines, plus cloud warehouse governance and security controls. - Ability to translate business needs into well-documented technical solutions and collaborate across teams.

Nice to have - A degree in computer science, engineering, or a related technical field. - Experience applying AI-assisted coding, automated testing, or language-model workflows to data development.

Benefits and work setup The role is described as remote-first. Listed benefits include vacation, wellness days and holidays, parental leave, a technology stipend, professional development, and a broader benefits package. The source gives a base salary range of $130,000–$170,000 per year; actual pay depends on factors including location and experience.