As an Analytics Engineer, your mission will be to provide clean and accurate data sets to end users, modeling data in a way that empowers end users to answer their own questions. You will work to apply software engineering best practices to the production and maintenance of analytics code and transform raw data into consumable information and business logic. As a member of our Data Analytics team, you will work closely with our Senior Data Scientist and Marketing Data Analyst to provide data-driven insights that inform key business decisions.

OUR TECHNOLOGY

Our Data Analytics stack utilizes Snowflake, dbt, Stitch / Fivetran, Amplitude and Omni.

WHAT YOU’LL DO EVERY DAY

• Support and contribute to the analytics layer of our team’s data environment to make data standardized and easily accessible to end users

• Integrate new data sources and build ingestion pipelines for our data warehouse

• Write production-quality ELT/ETL data transformation code with an eye for performance, maintainability and scalability

• Help bridge the gap between understanding business needs and knowing how to design efficient, usable data models

• Diagnose and fix data discrepancies and maintain transparent code to ensure business requirements and consistent ETL logic

• Collaborate with stakeholders in our growth marketing, merchandise planning, digital product, and finance & operations departments to define business questions and identify opportunities for data-driven improvements

• Build and maintain dashboards in Looker to deliver insights and help non-technical stakeholders be able to regularly track KPIs

• Document and communicate data insights and recommendations to stakeholders across the company and advocate for a data-driven culture internally and externally

WHAT WILL SET YOU UP FOR SUCCESS

• Curiosity and creative problem-solving skills

• An experienced “full-stack” analyst (a.k.a. analytics engineer), with 5+ years of experience in data science, data analysis, data engineering, or a relevant analytical/quantitative field

• Advanced SQL skills; experience with Python and/or R is a plus

• Experience with Snowflake, dbt, Stitch, and Looker (or similar tools) preferred

• Knowledge of data warehousing best practices

• Excellent communication skills—being someone who values building relationships with colleagues and enjoys explaining complex topics in simple terms

• Highly motivated to work autonomously with strong organizational and time management skills