Full-Time

Staff Data Engineer / Tech Lead

Distribution Center

Updated on 9/4/2026

Afresh

Afresh

51-200 employees

AI-driven inventory optimization for grocery retailers

Compensation Overview

CA$148k - CA$222k/yr

Remote in Canada

Remote

Category
Data & Analytics (1)
Required Skills
Python
Apache Spark
SQL
Machine Learning
Data Engineering
Databricks
Snowflake

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Requirements
  • Significant experience designing and maintaining extract-transform-load (ETL) processes that process large-scale datasets.
  • Proficiency with Python, PySpark, and SQL, and experience working with platforms or tools such as Databricks, Snowflake, or dbt.
  • At least 2 years of experience in a technical lead role, such as Tech Lead or Engineering Manager, with a willingness to mentor and help others grow.
  • Ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions.
  • Experience working directly with complex, unclean datasets and finding ways to process and analyze them.
  • Ability to identify areas where tooling or automation can simplify workflows and reduce manual effort.
  • Ability to explain ideas clearly to technical and non-technical audiences.
Responsibilities
  • Design, build, and optimize robust ETL processes using PySpark and dbt to process large-scale customer datasets.
  • Develop tools and frameworks to streamline data integrations and improve scalability.
  • Define the technical vision for Distribution Center data architecture.
  • Mentor engineers and manage external contractors to ensure the team delivers high-quality, practical solutions for current and future needs.
  • Partner with product, engineering, and applied science teams to scope work and deliver data solutions addressing customer data quality and product feature requirements.
Desired Qualifications
  • Ability to balance technical rigor with practical outcomes and execution.

Afresh offers an AI-powered platform that helps grocery retailers manage fresh food inventory to reduce waste and improve margins. Retailers connect POS data and supplier feeds; Afresh analyzes sales, spoilage risk, and shelf-life to generate restock recommendations and waste-avoidance guidance. It focuses on perishable items and uses retailer data for continuous learning, unlike generic inventory tools. Its goal is to meet customer demand while cutting waste and boosting profitability in the fresh food supply chain.

Company Size

51-200

Company Stage

Series B

Total Funding

$147.8M

Headquarters

San Francisco, California

Founded

2017

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Simplify Jobs

Simplify's Take

What believers are saying

  • Afresh raised $34 million in April 2026 to scale beyond produce into the entire store.
  • Stater Bros. rolled out Afresh chain-wide across 169 stores in January 2025.
  • Afresh reported 70% year-over-year revenue growth in 2025 and broader retailer penetration.

What critics are saying

  • Albertsons launched competing AI shopping assistants in August 2026, reducing Afresh's strategic leverage.
  • Afresh still depends on grocery operators adopting enterprise software, and retailer churn kills expansion.
  • If fresh-suite adoption stalls after the 2026 $34 million raise, Afresh becomes a niche ordering tool.

What makes Afresh unique

  • Afresh runs fresh-specific AI across 12,500 departments and 40 states by April 2026.
  • Its 2025 Fresh Store Suite expands from produce ordering into broader fresh workflows.
  • Wakefern chose Afresh's Fresh Buying in November 2025 for AI-powered fresh purchasing.

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Benefits

Comprehensive health plans

Competitive compensation

Generous parental leave

Equity packages

401(k) matching

Flexible vacation policy

Monthly grocery stipend

Professional development program