September 25
β’ Afresh is on a mission to eliminate food waste and make fresh food accessible to all. β’ Our first A.I.-powered solution optimizes ordering, forecasting, and store operations for fresh food departments in brick-and-mortar grocers. β’ The Data Science and Analytics team collaborates closely with every team in the company, empowering them to build products and make decisions with data. β’ As a staff data engineer on the Data Science team, you will own the development of our analytics platform. β’ This is a high-impact role with ownership of highly visible projects and a lot of room to grow in your scope. β’ Founded in 2017, Afresh is working on the #1 solution to curb climate change: reducing food waste.
β’ 6+ years of experience as an data engineer, analytics engineer, data warehouse engineer, or a similar role. β’ Strong understanding of advanced concepts in SQL. β’ Exceptional communication and leadership skills, with a proven ability to facilitate cross-team and cross-functional collaboration and information sharing. β’ 1+ years of experience working with SQL-driven transform libraries that support an ELT paradigm, like dbt or sqlmesh, at scale, including setting up CI/CD pipelines that ensure high quality transformations. β’ Expert knowledge about the differences between OLTP and OLAP database design. β’ Familiarity with the differences between data engineering concepts like Data Mesh, Data Lake, Data Warehouse, Data Fabric, and Data Lakehouse. β’ Experience with setting up a semantic layer defined with code (LookML, Cube.dev, AtScale, dbt semantic layer). β’ Technologies: SQL, Python, Airflow, dbt, Snowflake/Databricks/BigQuery, Spark.
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