As an Analytics Engineer at Slash, you'll own our entire data stack - from warehouse architecture to end-user analytics. You'll build and maintain our data models, create impactful dashboards, and develop automated workflows that power our operations. Working closely with our product, sales, and engineering teams, you'll help scale our analytics infrastructure while ensuring data reliability and accessibility across the organization.

What you'll be doing:

• Design and implement scalable DBT models that transform billions of dollars in transaction data into analytics-ready datasets

• Own end-to-end data pipelines, from source system integration through dashboard delivery

• Create and maintain documentation for data models, business logic, and metric definitions

• Develop and optimize complex SQL transformations to support business intelligence and reporting needs

• Partner with stakeholders to define key metrics

• Develop automated workflows & reporting systems that enable self-serve analytics

• Build cohort analysis and retention tracking systems to drive business insights

• Define and implement data modelling standards and best practices

• Work with product and sales teams to instrument new features and establish metrics tracking

We're looking for someone who:

• Has 3+ years of experience in analytics engineering, data analytics, or similar role

• Is comfortable working across the data stack & wearing multiple hats.

• Brings experience with modern data stack (e.g., Snowflake, DBT, Retool/Looker/Sigma)

• Can effectively collaborate with both technical and non-technical stakeholders

• Demonstrates strong experience with data modelling concepts

• Has experience building automated workflows and operational tools

• Shows ability to balance technical implementation with business needs

• Demonstrates strong documentation skills and attention to detail

• Has experience implementing analytics engineering best practices at scale