Application Guide

How to Apply for Senior Staff Data Engineer

at Afresh Technologies

🏢 About Afresh Technologies

Afresh Technologies is an AI-driven platform tackling the massive problem of food waste in the fresh food supply chain, reducing millions of pounds of waste annually. Their mission-driven approach combines cutting-edge AI with real-world impact, making it a compelling place for engineers who want their work to matter. The remote-first culture and focus on innovation in data engineering offer a unique opportunity to shape core systems from the ground up.

About This Role

As a Senior Staff Data Engineer, you will architect and build the core data systems and pipelines that power Afresh’s AI products, owning reliability and quality from raw data to production. You’ll tackle ambiguous, high-leverage problems, set technical direction, and champion AI-forward engineering to accelerate development. This role is pivotal in scaling the platform to reduce food waste globally.

💡 A Day in the Life

A typical day might start with a standup with the data engineering team to discuss pipeline health and priorities, then dive into designing a new data model in dbt or optimizing a PySpark job on Databricks. You’ll likely have cross-functional syncs with product and customer teams to understand data needs, and spend focused time coding, reviewing PRs, or documenting architecture decisions. The day ends with monitoring pipeline performance and iterating on reliability improvements.

🚀 Application Tools

Generate Cover Letter

AI-powered, tailored for Afresh Technologies

Interview Prep

Practice questions for this role

🎯 Who Afresh Technologies Is Looking For

  • You have 8+ years of data engineering experience at a staff or principal level, with deep expertise in Python, PySpark, SQL, dbt, Airflow, and modern data platforms like Databricks or Snowflake.
  • You thrive in ambiguity, taking undefined problems and driving them to shipped solutions without waiting for detailed specs.
  • You have a proven track record of setting technical direction, defining architecture and abstractions that make data pipelines faster, cleaner, and more repeatable.
  • You excel at cross-functional collaboration, influencing product and customer-facing teams to align on data quality and reliability standards.

📝 Tips for Applying to Afresh Technologies

1

Highlight specific examples where you architected end-to-end data pipelines from raw data to production, emphasizing reliability and quality metrics.

2

Mention experience with AI-forward engineering, such as using ML models to improve data quality or automate pipeline monitoring.

3

Showcase your ability to handle ambiguity: describe a project where you defined the problem scope and solution without a detailed spec.

4

Tailor your resume to include keywords like 'dbt', 'Airflow', 'Databricks', 'Snowflake', and 'PySpark' prominently, as these are core to the stack.

5

Quantify impact: use numbers to show how your work reduced food waste, improved pipeline efficiency, or accelerated product delivery.

✉️ What to Emphasize in Your Cover Letter

['Emphasize your passion for Afresh’s mission to reduce food waste and how your data engineering skills directly contribute to that impact.', 'Describe your experience with ambiguous, high-leverage problems and how you drove them to shipped solutions.', 'Highlight your technical expertise in the required tools (Python, PySpark, SQL, dbt, Airflow, Databricks/Snowflake) with concrete examples.', 'Show your ability to set technical direction and influence cross-functional teams, aligning with Afresh’s collaborative culture.']

Generate Cover Letter →

🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Read Afresh’s blog posts or press releases about their AI-driven platform and impact on food waste reduction.
  • → Understand the fresh food supply chain challenges and how data engineering can optimize inventory, reduce waste, and improve efficiency.
  • → Review the company’s tech stack (Databricks, Snowflake, dbt, Airflow) and think about how you would improve or scale it.
  • → Look for any recent engineering talks or presentations by Afresh engineers to understand their culture and technical challenges.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Describe a time you architected a data pipeline from scratch; how did you ensure reliability and quality?
2 How do you approach ambiguous problems? Walk through a specific example where you defined the solution without a detailed spec.
3 Explain your experience with dbt and Airflow; how have you used them to improve data pipeline maintainability?
4 How do you champion AI-forward engineering? Give an example of using ML or AI to accelerate data engineering tasks.
5 How do you collaborate with product and customer-facing teams to align on data quality and pipeline reliability?
Practice Interview Questions →

⚠️ Common Mistakes to Avoid

  • Don’t be vague about your experience: provide specific examples of pipelines you built, tools used, and impact achieved.
  • Avoid focusing only on batch processing; Afresh likely needs real-time or near-real-time data for fresh food supply chain.
  • Don’t underestimate the importance of collaboration: this role requires influencing product and customer teams, so highlight soft skills.

📅 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!

← Back to Job Listing Apply Now →