Senior Data Engineer

Join Grailed, a leading fashion resale marketplace, as a Senior Data Engineer. In this hands-on role, you will be responsible for building and scaling the data infrastructure that powers the business. You will work closely with a tight-knit team of data partners, engineers, product managers, marketers, and executive leadership. Your key responsibilities will include ensuring the reliability, availability, and accuracy of the data infrastructure, building and maintaining the data pipeline, and championing data governance. The ideal candidate will have 5+ years of engineering experience, strong SQL skills, and proficiency in Python.

• Assurer la fiabilité, la disponibilité et l'exactitude de notre infrastructure de données, en veillant à la conformité aux normes de confidentialité des données.
• Construire, maintenir et améliorer notre pipeline de données en utilisant notre pile de données moderne (Snowflake, DBT, Airflow, Looker).
• Collaborer étroitement avec les analystes, les chefs de produit, les ingénieurs, le marketing, le juridique, la fraude et d'autres parties prenantes, en traduisant les besoins commerciaux en solutions de données exploitables.
• The strongest candidates will have enough breadth of experience across different roles and environments to know that building it right matters as much as building it at all
• Experience building and consuming APIs
• Experience with our stack: Snowflake, DBT, Airflow, Fivetran, Segment, Looker, Amplitude, Algolia, AWS/Lambda, Git
• Deep experience building, maintaining, and architecting data pipelines end-to-end, ingestion through consumption
• Strong SQL skills and proficiency in Python
• 5+ years of engineering experience, with a strong foundation in software and data engineering, and familiarity with analytics engineering
• Has driven projects from scoping through delivery, owning the outcomes and not just the tasks, comfortable sitting with ambiguity but driven to resolve it
• Pragmatic about technology choices, the goal is solving business problems, not chasing the latest tools
• Comfortable operating with a high degree of autonomy, self-directed and able to drive work forward, while keeping the team informed and aligned along the way
• Treats data quality and observability as first-class concerns, comfortable implementing monitoring and alerting practices that catch issues before the business does
• Builds with the team in mind, systems that are intuitive, approachable, and easy for others to understand, extend, and maintain
• Naturally elevates the data literacy of those around them by educating and guiding stakeholders toward better data practices
• Strong communicator, equally effective with engineers and non-technical stakeholders
• Familiarity with ML/data science workflows and how data engineering supports them
• Exposure to search and discovery platforms
• Prior experience in retail, resale, or marketplace commerce, genuine curiosity about the domain a must regardless