Remote Staff Data Engineer

Summary

Join Afresh on a mission to eliminate food waste and make fresh food accessible to all. As a staff data engineer, you will own the development of our analytics platform, improving and extending our data analytics architecture, collaborating with engineers and product managers, evolving our existing data quality and governance processes, and mentoring other engineers.

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

Responsibilities

• Improve and extend our data analytics architecture to provide reliable and accessible data for a wide range of use cases
• Collaborate with engineers, product managers, and data scientists to understand their data needs, and then build extensible dimensional models and semantic layer metrics that allow for consistent and reliable insights
• Evolve our existing data quality and data governance processes
• Mentor and up-skill other engineers