Application Guide

How to Apply for Staff Software Engineer Data - DC Tech Lead

at Afresh Technologies

🏢 About Afresh Technologies

Afresh Technologies is on a mission to eliminate food waste using AI, targeting the fresh food supply chain where waste is rampant. Their platform optimizes ordering and distribution for grocery retailers, reducing millions of pounds of waste annually. Working here means applying cutting-edge data engineering to a tangible environmental problem with measurable impact.

About This Role

As Staff Software Engineer Data - DC Tech Lead, you'll own the data architecture for distribution centers, building scalable ETL pipelines that process massive datasets from retailers. You'll lead a team of engineers and contractors, collaborating with product and science teams to deliver data solutions that directly reduce waste. This role combines technical depth with strategic leadership in a mission-driven company.

💡 A Day in the Life

Start with a stand-up with your team of engineers and contractors, reviewing progress on ETL pipelines. Spend the morning designing a new data model for a retailer's inventory feed, then pair with a data scientist to refine a feature for waste prediction. After lunch, mentor a junior engineer on PySpark optimization, and end the day reviewing a contractor's pull request and updating the tech roadmap.

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Interview Prep

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🎯 Who Afresh Technologies Is Looking For

  • Experienced in designing and maintaining ETLs processing terabytes of data daily, with proficiency in PySpark, Python, SQL, and tools like Databricks, Snowflake, or DBT.
  • Proven tech lead with 2+ years guiding teams, making architectural decisions, and managing external contractors in a fast-paced environment.
  • Comfortable with ambiguity—able to take vague requirements from product and science teams and turn them into robust data solutions.
  • Passionate about sustainability and reducing food waste, and motivated by applying data engineering to real-world impact.

📝 Tips for Applying to Afresh Technologies

1

Highlight specific ETL projects where you processed large-scale datasets (e.g., >10TB) using PySpark or similar; mention data volume and complexity.

2

Emphasize your tech lead experience: describe how you mentored engineers, made architectural decisions, and managed contractors or vendors.

3

Show familiarity with Afresh's mission: mention food waste or sustainability in your cover letter or resume summary.

4

Tailor your resume to include keywords like 'PySpark', 'DBT', 'Databricks', 'Snowflake', and 'distributed systems'.

5

Provide a concise example of how you handled ambiguous requirements—e.g., 'took a high-level product goal and defined data pipelines to support it'.

✉️ What to Emphasize in Your Cover Letter

["Your passion for reducing food waste and how your data engineering skills can directly contribute to Afresh's mission.", 'Specific examples of leading data architecture for large-scale ETLs, including tools like PySpark and DBT.', 'Your experience as a tech lead: mentoring, managing contractors, and aligning technical vision with business goals.', 'How you thrive in ambiguous environments and partner with cross-functional teams (product, science) to deliver solutions.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Read Afresh's blog and case studies to understand their current data architecture and the impact of their platform on retailers like Albertsons.
  • → Research the fresh food supply chain challenges—e.g., perishability, demand variability—to speak knowledgeably about data needs.
  • → Look into Afresh's engineering culture and values on their careers page or Glassdoor to align your answers with their team principles.
  • → Check recent news or press releases about Afresh's growth, funding, or partnerships to show you're up-to-date.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Design a scalable ETL pipeline for processing daily store-level inventory data from hundreds of retailers into a data warehouse.
2 How would you handle data quality issues in streaming vs. batch ETLs? Give a real example from your experience.
3 Describe a time you led a team through a major technical decision—e.g., choosing between Databricks and Snowflake for a use case.
4 How do you mentor engineers and manage external contractors to ensure delivery while maintaining code quality?
5 Explain how you would partner with a data scientist to turn a research model into a production ETL pipeline.
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⚠️ Common Mistakes to Avoid

  • Focusing only on technical skills without showing leadership or impact—this role requires tech lead experience, not just coding.
  • Giving generic answers about ETLs; be specific about scale (data volume, latency requirements) and tools (PySpark, DBT).
  • Ignoring the mission—candidates who don't express genuine interest in food waste reduction may seem misaligned.

📅 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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