Analytics Engineer, Loop

• 2+ years experience building analytical products (system, dashboard, models)
• Strong proficiency in SQL and Python for data transformations and automation
• Hands-on experience with modern data stack tools (e.g., Snowflake, dbt, Dagster, Airflow, Looker)
• Excellent business communication skills to translate data insights into actionable business strategies
• Experience with data dashboarding and visualization tools (e.g., Tableau, Looker, Superset, Mode)
• Ability to manage, optimize, and scale data infrastructure

Desirable

• As an Analytics Engineer at Loop, you will play a pivotal role in maturing the data organization. You’ll work cross-functionally to design, build, and own the core infrastructure and data models. These systems will enable both internal and client facing analytics, accelerating data-driven decision-making throughout the company and our clients
• Own Core Data Models and ETL Pipelines: Design, build, and maintain Loop’s core data models and ETL processes
• Define Metrics and Governance: Establish and govern key business metrics for consistency across teams
• Maintain Data Quality and Uptime: Ensure data accuracy and reliability with strong SLAs
• Automate Data Requests: Convert ad-hoc data requests into scalable, repeatable pipelines
• Optimize Data Infrastructure: Manage and optimize data infrastructure for performance, cost, and compliance
• Develop Data Products: Create data-driven solutions and embedded analytics to support business and product teams