Application Guide

How to Apply for Senior Data Engineer

at Afresh Technologies

🏢 About Afresh Technologies

Afresh Technologies is an AI-driven platform uniquely focused on reducing millions of pounds of food waste annually in the fresh food supply chain. Their mission-driven approach combines cutting-edge technology with tangible environmental impact, making it an attractive workplace for engineers who want their work to contribute to sustainability and food system efficiency.

About This Role

As a Senior Data Engineer at Afresh, you'll be responsible for scaling customer data integrations and processing billions of records using PySpark and DBT. This role directly impacts the company's ability to onboard customers faster and provide reliable data for reducing food waste, making it crucial for both business growth and mission fulfillment.

💡 A Day in the Life

A typical day involves developing and optimizing PySpark ETLs to process customer datasets, collaborating with product teams to design data solutions for new features, and investigating new technologies to improve the data platform. You'll spend time building integration frameworks to streamline customer onboarding and ensuring data reliability for downstream use in reducing food waste.

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Interview Prep

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🎯 Who Afresh Technologies Is Looking For

  • Has extensive experience designing and maintaining ETL pipelines for large-scale datasets, specifically with PySpark and DBT
  • Is proficient in Python, SQL, and has hands-on experience with platforms like Databricks or Snowflake
  • Demonstrates strong problem-solving skills and can work effectively with ambiguous requirements to deliver concrete solutions
  • Has experience collaborating with cross-functional teams (product, engineering, go-to-market) to design data solutions for new features

📝 Tips for Applying to Afresh Technologies

1

Highlight specific experience with PySpark and DBT in processing large datasets, quantifying scale (e.g., 'processed X billion records')

2

Emphasize projects where you streamlined customer data integrations or improved onboarding processes

3

Showcase examples of implementing new technologies to solve practical data platform pain points

4

Demonstrate understanding of Afresh's mission by linking your data engineering experience to sustainability or supply chain impact

5

Include concrete examples of collaborating with non-technical teams to deliver data solutions

✉️ What to Emphasize in Your Cover Letter

['Your experience with PySpark and DBT in processing large-scale customer datasets', 'Specific examples of building tools/frameworks that streamlined customer integrations or onboarding', 'How your problem-solving approach aligns with working on ambiguous requirements in a mission-driven environment', "Why you're passionate about applying data engineering skills to reduce food waste and improve supply chains"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Afresh's specific impact metrics on food waste reduction and their customer case studies
  • → The company's technology stack mentions (Databricks, Snowflake) and how they might be applied in their context
  • → Recent news about Afresh's growth, funding, or partnerships in the food supply chain space
  • → The challenges of fresh food supply chains and how data could address spoilage and inefficiency

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk me through your experience designing and maintaining ETL pipelines with PySpark and DBT at scale
2 How would you approach streamlining customer data integrations for faster onboarding?
3 Describe a time you implemented a new technology to solve a data platform pain point
4 How do you collaborate with product and go-to-market teams to design data solutions for new features?
5 What interests you about applying data engineering to food waste reduction and the fresh food supply chain?
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⚠️ Common Mistakes to Avoid

  • Applying with only generic data engineering experience without highlighting PySpark/DBT or large-scale ETL work
  • Focusing solely on technical skills without showing interest in Afresh's mission or the food supply chain domain
  • Presenting yourself as needing clear requirements rather than demonstrating ability to work with ambiguity

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Afresh Technologies!

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