Analytics Engineer
Build and own core data models, ETL pipelines, and analytics infrastructure to enable data-driven decisions across the company and clients. Requires 2+ years building analytical products, strong SQL/Python, and modern data stack experience.
What you will do
- 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.
Qualifications
- 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.
Nice to Have
- Global supply chain experience in transportation and logistics.
- Previous experience setting up a data stack in a startup from scratch.
- Interest or experience in working with cutting-edge open-source data tool.
- Proven ability to convert ad-hoc data requests into scalable, automated pipelines.
- Experience working in the logistics domain.
Compensation & Benefits
- Base pay 135k - 155k
- Health insurance, dental insurance, vision insurance, 401(k) plan, paid time off, paid holidays, parental leave, and other company-sponsored benefits.
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