Senior Data Engineer, Procurement Sciences AI

• Strong foundation in Data Engineering with production deployment experience with multiple orchestrators
• Excited about the challenge of bringing disparate data under one roof and defining the data models that will take the business to the next level
• Collaborative problem solver who thrives in startup environments with evolving requirements
• Eager to learn new technologies while leveraging proven Data Engineering practices
• 5+ years building production data pipelines with real user data at scale
• Deep SQL and Python expertise - you think in sets and write maintainable tested code
• Experience with modern data stack BigQuery (or Snowflake/Redshift), dbt or similar transformation tools, orchestrators like Airflow or Dagster
• Track record of architectural thinking making design decisions that lasted and can articulate the tradeoffs
• Experience with event-driven architectures (Kafka, Pub/Sub, SQS) and streaming vs. batch tradeoffs
• While formal education is not a strict requirement, a Bachelor's or Master’s degree in Computer Science, Engineering, or a related field is preferred

Desirable

• We are seeking a Data Engineer to build our customer and backend pipelines
• You'll work closely with our Data and AI leadership to design and implement greenfield orchestrated data systems, including data ingestion from the product and building Source of Truth customer and finance tables
• In this role, you will own the design, implementation and iterative improvement of all our data and how it gets used by various cross functional teams
• Your work will directly impact product performance by providing the data to build and train recommendation and search models, maintaining product data flows, and servicing the needs of finance and ops
• You'll collaborate with a talented team to solve real technical problems in a fast-growing SaaS environment
• Build, deploy, and maintain production data ingestion on top of our data platform
• Design and implement feature engineering and source of truth tables for finance and product usage metrics
• Lay the foundation for a future analytics team to empower the business to make data driven decisions and fast experimental iteration
• Collaborate with ML and engineering teams to support the needs to train large scale models for in production use

• As part of our employment process, a background check is required. The background check may include a review of your credit history, criminal records, and employment verification, among other items