Data Engineer
Stord
- United States, United States
- Remote
- Posted May 18, 2026
Job description
About the role
The Senior Data Engineer will design, develop and maintain scalable data pipelines, lead the re‑architecture of Stord’s data warehouse, build and optimize GCP‑based data lakes and warehouses, and support machine‑learning applications, collaborating with data analysts, product managers and engineering teams to deliver data solutions that drive business value.
About the company
Stord is the Consumer Experience Company, providing end‑to‑end commerce solutions that combine high‑volume fulfillment services with a technology platform (OMS, WMS, pre‑ and post‑purchase) to help DTC and B2B brands improve checkout, shipping and margins. It manages over $10 billion of commerce annually, is headquartered in Atlanta with facilities across the United States, Canada and Europe, and is backed by investors such as Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford and Salesforce Ventures.
Requirements
- 5+ years of experience in data engineering or a related field
- Proven experience building and maintaining data pipelines and data warehouses
- Experience with cloud platforms, preferably GCP
- Strong proficiency in SQL and Python
- Experience with data transformation tools such as dbt or similar
- Experience with data pipeline tools (e.g., Apache Airflow, Prefect, or similar)
- Experience with data warehousing technologies (e.g., BigQuery, Snowflake)
- Familiarity with data lake concepts and technologies
- Understanding of data engineering best practices
- Understanding of basic machine learning concepts, data preparation techniques, and model evaluation
- Experience with version control systems (e.g., Git)
- Strong problem‑solving and analytical skills
- Excellent communication and collaboration skills
- Ability to work independently and as part of a team
- Strong attention to detail
- Bonus: basic understanding of data science concepts, common ML models, and statistical analysis
- Bonus: experience with machine learning data preparation
- Bonus: experience in the logistics or supply chain industry
- Bonus: experience in a startup environment