What are the responsibilities and job description for the Analytics Engineer position at Loop?
About Loop
Loop is on a mission to streamline the movement of money between shippers, carriers, and brokers to unlock margin and increase liquidity in the supply chain.
Today, logistics payments are a big black box that unnecessarily drains thousands, if not millions, of dollars. Legacy services do not meet the market's needs. Transportation teams need a solution that unlocks insights from their complex datasets, rather than drowning them in manual workflows.
Loop harnesses AI expertise with deep logistics industry knowledge to deliver automated audits, streamlined resolutions, expedited payments, and most importantly actionable insights. All so that shippers and 3PLs can improve spend visibility, eliminate unnecessary costs, and optimize their transportation spend. Loop’s customers see a 4% reduction in costs and an 80% boost in back-office productivity.
Loop is a customer-obsessed company that sees the complexity in the supply chain as an opportunity rather than a challenge. Our foundational AI capitalizes on the messiness in the system to maximize outcomes for our customers.
Investors include Founders Fund, 8VC, Susa Ventures, Flexport, and 50 industry-leading angel investors. Our team brings subject matter expertise and experience from companies like Uber, Google, Flexport, Meta, Samsara, Intuit, and Rakuten – as well as traditional logistics companies like CH Robinson.
About Role
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.
What you will do
Loop is on a mission to streamline the movement of money between shippers, carriers, and brokers to unlock margin and increase liquidity in the supply chain.
Today, logistics payments are a big black box that unnecessarily drains thousands, if not millions, of dollars. Legacy services do not meet the market's needs. Transportation teams need a solution that unlocks insights from their complex datasets, rather than drowning them in manual workflows.
Loop harnesses AI expertise with deep logistics industry knowledge to deliver automated audits, streamlined resolutions, expedited payments, and most importantly actionable insights. All so that shippers and 3PLs can improve spend visibility, eliminate unnecessary costs, and optimize their transportation spend. Loop’s customers see a 4% reduction in costs and an 80% boost in back-office productivity.
Loop is a customer-obsessed company that sees the complexity in the supply chain as an opportunity rather than a challenge. Our foundational AI capitalizes on the messiness in the system to maximize outcomes for our customers.
Investors include Founders Fund, 8VC, Susa Ventures, Flexport, and 50 industry-leading angel investors. Our team brings subject matter expertise and experience from companies like Uber, Google, Flexport, Meta, Samsara, Intuit, and Rakuten – as well as traditional logistics companies like CH Robinson.
About Role
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.
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.
- 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.
- 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.
- EPD (Engineering, Product, and Design): Become the data expert within the EPD organization, empowering data-driven decisions across product development and iterations
- Strategy and Operations: Enable product delivery teams (solutions, analyst) to deliver value to customers through actionable dashboards, metrics, and self-service reports
- AI Platform: Expedite the development of new models and training of existing models by simplifying the necessary data cleansing and preparation
- Base pay 135k - 155k
- Premium Medical, Dental, and Vision Insurance plans
- Insurance premiums covered 100% for you
- Unlimited PTO
- Fireside chats with industry leading keynote speakers
- Off-sites in locales such as Napa and Tahoe
- Generous professional development budget to feed your curiosity
- Physical and Mental fitness subsidies for yoga, meditation, gym, or ski memberships