Staff Data Engineer - Analytics

September 25

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Afresh

WebsiteLinkedInAll Job Openings

Grocery • AI • Machine Learning • Enterprise Software • Forecasting

51 - 200 employees

Founded 2017

🤖 Artificial Intelligence

🛍️ eCommerce

☁️ SaaS

Description

• Afresh is on a mission to eliminate food waste and make fresh food accessible to all. • Our first A.I.-powered solution optimizes ordering, forecasting, and store operations for fresh food departments in brick-and-mortar grocers. • The Data Science and Analytics team collaborates closely with every team in the company, empowering them to build products and make decisions with data. • As a staff data engineer on the Data Science team, you will own the development of our analytics platform. • This is a high-impact role with ownership of highly visible projects and a lot of room to grow in your scope. • Founded in 2017, Afresh is working on the #1 solution to curb climate change: reducing food waste.

Requirements

• 6+ years of experience as an data engineer, analytics engineer, data warehouse engineer, or a similar role. • Strong understanding of advanced concepts in SQL. • Exceptional communication and leadership skills, with a proven ability to facilitate cross-team and cross-functional collaboration and information sharing. • 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. • Expert knowledge about the differences between OLTP and OLAP database design. • Familiarity with the differences between data engineering concepts like Data Mesh, Data Lake, Data Warehouse, Data Fabric, and Data Lakehouse. • Experience with setting up a semantic layer defined with code (LookML, Cube.dev, AtScale, dbt semantic layer). • Technologies: SQL, Python, Airflow, dbt, Snowflake/Databricks/BigQuery, Spark.