About the Role

Fashion Nova is seeking a Lead Data Engineer to help build and scale the data platform that powers our next phase of growth. This role will be instrumental in designing, developing, and optimizing the data infrastructure that supports analytics, reporting, operational decision-making, and customer insights across the organization.

As a technical leader, you will drive best practices in data modeling, pipeline development, data quality, and platform performance while partnering closely with Analytics, Product, Engineering, and Business stakeholders. You will play a critical role in shaping the architecture, scalability, and reliability of Fashion Nova's modern data ecosystem.

Responsibilities

• Design, build, and maintain scalable, production-grade data pipelines and transformation frameworks using Snowflake and dbt.
• Lead data modeling efforts to support reporting, analytics, and business intelligence initiatives across multiple business functions.
• Optimize Snowflake performance, storage, and cost efficiency through best practices in architecture and query design.
• Develop and maintain orchestration workflows using Airflow, Dagster, or similar tools.
• Build and maintain Python-based solutions for data processing, automation, and integration.
• Partner with Analytics, Product, Engineering, and business stakeholders to translate business requirements into scalable data solutions.
• Implement and maintain CI/CD processes, testing frameworks, and deployment strategies for data transformations and pipelines.
• Establish and enforce best practices for data quality, observability, monitoring, and reliability.
• Drive data security, governance, and compliance initiatives across the data platform.
• Evaluate and implement Snowflake features including Time Travel, Zero-Copy Cloning, Secure Data Sharing, and other platform capabilities.
• Support integration of data warehouse solutions with BI, reporting, and analytics platforms.
• Mentor junior engineers and contribute to the growth of the data engineering team.
• Participate in architecture discussions, technical planning, and strategic roadmap initiatives.
• Troubleshoot complex data challenges and make sound technical decisions in a fast-paced environment.

Requirements

• 7+ years of experience in data engineering
• Of those 7 years, Senior-level experience required: 1 year or more
• Strong experience with Snowflake: data modeling, performance optimization, security implementation.
• Proficient in dbt development, building production-grade data transformation pipelines.
• Advanced SQL skills and Snowflake-specific features (Time Travel, Zero-Copy Cloning, Secure Data Sharing).
• Experience with data orchestration tools: Airflow or Dagster acceptable.
• Python skills for data processing and automation.
• Hands-on experience in data warehouse design, optimization, and integration with analytics tools.
• Knowledge of CI/CD, testing, and deployment strategies for data transformations.
• Experience with data security best practices and monitoring solutions.
• Excellent communication and collaboration skills in agile environments.
• Strong problem-solving skills and ability to make independent technical decisions.
• Certification in Snowflake or dbt
• Experience with cloud platforms: AWS, GCP, or Azure
• Familiarity with data governance and compliance requirements

Benefits