Data Engineer

Furniture.com is a high growth consumer tech start up that is addressing fundamental challenges in the $200B US furniture space. The company is a B2B and B2C digital aggregator with a simple mission: To make finding furniture easy.

For consumers, we make it easy to find the right furniture by enhancing search and streamlining the end-to-end customer experience. For retail partners, we deliver a digital platform allowing them to expand their reach with a high-intent, high value furniture audience.

Furniture.com is growing fast. We are backed by the investment arm of one of America’s largest furniture retailers, although we are independent and proudly building a technology in service of the furniture industry and furniture shoppers.

We’re looking for a Data Engineer to be part of a fast-paced, exciting data engineering team. This role requires deep hands-on knowledge of Spark (preferably PySpark), Databricks (Unity Catalog, Pipelines, Asset Bundles), and SQL. You will have a head start here if you have prior experience with NoSQL databases, key-value stores, and graph databases, and are excited about building scalable, production-grade data products.

• →Own a feature development end to end, from data model design to production deployment.
• →Use AI-assisted tools confidently to improve the speed, quality, and efficiency of your work, including design and code output:
  • →Apply AI tools to streamline workflows and accelerate delivery.
  • →Maintain high standards for quality in both design and engineering output.
• →Be comfortable working in an AI-forward environment where this approach is part of the team’s operating model.
• →Partner with Data Science, Product, Engineering, and Business stakeholders to ensure alignment and delivery of value.

We are an equal opportunity employer. We do not discriminate in hiring or employment against any individual based on race, color, gender, national origin, ancestry, religion, disability, age, veteran status, sexual orientation, gender identity or expression, marital status, pregnancy, citizenship, or any other factor protected by law.

Applicants must be authorized to work in the U.S.

• 3+ year in data engineering, 1+ in Databricks
• Hands-on, working experience with:
  • Python, SQL, Spark/PySpark
  • ETL/ELT orchestration tools like Airflow, dbt, etc.
  • Databricks
• Awareness of data engineering best practices and when to be pragmatics
• Collaborative experience with Data Scientists, Product Managers, and cross-functional teams.
• Good communication skills