Take ownership of the company’s data stack, including BigQuery and Looker Studio environments
Build and maintain real-time reporting pipelines for marketing spend and campaign performance
Implement and manage tracking pixels, server-to-server (S2S) integrations, and event tracking systems
Design and improve attribution models to support data-driven marketing decisions
Serve as the technical point of contact for the User Acquisition team regarding tracking, APIs, URLs, naming conventions, and troubleshooting
Develop automation solutions to improve reporting workflows and operational efficiency
Build inventory forecasting pipelines across Shopify, Amazon, TikTok Shop, and other ecommerce channels
Collaborate cross-functionally with marketing, operations, and analytics stakeholders to improve reporting accuracy and business visibility

6+ years of experience in data engineering, preferably within ecommerce or DTC environments
Strong SQL and data modeling skills
Hands-on experience with BigQuery, Snowflake, or similar cloud data warehouses
Proficiency in Python for automation and data processing
Experience with modern data stack tools such as dbt and Airflow
Experience with BI and visualization tools such as Looker Studio, Looker, Tableau, or Power BI
Strong understanding of marketing data ecosystems, including APIs, tracking pixels, S2S integrations, and event tracking
Familiarity with Shopify, Amazon Seller Central, Google Ads, and Meta Ads
Excellent communication skills in English
Comfortable working independently in a remote environment
Nice to have: Experience with Kubernetes and Docker
Nice to have: Experience with GCP or broader cloud infrastructure environments
Nice to have: Experience supporting attribution, ecommerce analytics, or growth marketing teams

Data Engineer

Key skills