Senior Data Engineer

🕒 April 21

🏈 Alabama, California, +19 more states – Remote

🏈 Alabama – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🐊 Florida – Remote 🌽 Illinois – Remote 🐎 Kentucky – Remote 🦬 Montana – Remote 🎰 Nevada – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🌲 Oregon – Remote 🍂 Massachusetts – Remote 🚗 Michigan – Remote 🏰 Missouri – Remote 🔔 Pennsylvania – Remote 🤠 Texas – Remote ⛷️ Utah – Remote ⚔️ Virginia – Remote ☕ Washington – Remote 🧀 Wisconsin – Remote

💵 $156k - $211k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Afresh

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

🤖 Artificial Intelligence

🛍️ eCommerce

☁️ SaaS

Artificial Intelligence • eCommerce • SaaS

Afresh is a technology company that provides innovative solutions for the fresh food grocery sector. Their platform leverages cutting-edge machine learning to optimize ordering, inventory management, and reduce food waste, helping grocery teams to manage fresh produce more efficiently. Afresh aims to transform grocery store operations with best-in-class technology, ensuring fresher displays, faster inventory turns, and increased sales. By enhancing operational efficiency and accuracy, Afresh supports grocers in sustainability goals like reducing greenhouse gas emissions and water usage. The company is committed to sustainably nourishing the world with fresh food.

📋 Description

• Build tools and frameworks that streamline customer integrations, enabling faster onboarding and better handling of customer data. • Create robust ETLs in PySpark and DBT to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use. • Investigate and implement new technologies into the data platform, focusing on practical solutions that address current pain points and anticipate future needs. • Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features. • Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations. • Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need. • Support team members by mentoring engineers, leading technical discussions, and providing clear, actionable feedback.

🎯 Requirements

• Significant experience designing and maintaining ETLs that process large-scale datasets. • Proficiency with Python, PySpark, SQL, and experience working on platforms/tools like Databricks, Snowflake, or DBT. • Strong problem-solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions. • A focus on practical outcomes—you're skilled at balancing technical rigor with the need to get things done. • Experience working directly with complex, unclean datasets and finding innovative ways to process and analyze them. • A knack for identifying areas where tooling or automation can simplify workflows and reduce manual effort. • Excellent communication skills—you’re able to explain your ideas clearly to both technical and non-technical audiences. • Proven leadership in technical projects, with a willingness to mentor and help others grow.

🏖️ Benefits

• Join a mission-driven company reducing millions of pounds of food waste in grocery stores per year. • Work on challenging, real-world problems that have a direct impact on our customers. • Be part of a collaborative, supportive team where your ideas are valued and acted on. • Use cutting-edge tools and platforms to solve meaningful data challenges.