Staff Data Engineer, Analytics

A Fresh - San Francisco, CA

Full-time - Mid Level

San Francisco, CA

About the position

As a Staff Data Engineer at Afresh, you will play a crucial role in developing and enhancing the analytics platform that supports the company's mission to reduce food waste. This position involves collaborating with various teams to create reliable metrics from diverse data sources, enabling data-driven decision-making and improving reporting products for customers. You will be responsible for evolving the data warehouse schema, establishing data governance patterns, and mentoring other engineers, all while working on high-impact projects that contribute to the company's social mission.

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 build extensible dimensional models and semantic layer metrics
• Evolve our existing data quality and data governance processes
• Mentor and up-skill other engineers

Requirements

• 6+ years of experience as a 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
• 1+ years of experience working with SQL-driven transform libraries that support an ELT paradigm, like dbt or sqlmesh, at scale
• Expert knowledge about the differences between OLTP and OLAP database design
• Familiarity with 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)

Nice-to-haves

• Experience with technologies such as Python, Airflow, Snowflake, Databricks, BigQuery, and Spark

Benefits

• Remote work flexibility for employees residing in specified states
• Opportunity to work on impactful projects that contribute to reducing food waste
• Collaborative and inclusive work environment