Application Guide

How to Apply for Senior Data Engineer - Data Platform and Analytics

at Worldly

🏢 About Worldly

Worldly is unique as the world's most comprehensive impact intelligence platform, providing businesses with real data on supply chain impacts. This mission-driven company combines technology with sustainability, offering the opportunity to work on meaningful data that helps companies make responsible decisions. Their focus on impact intelligence makes them a leader in the growing ESG (Environmental, Social, Governance) data space.

About This Role

This Senior Data Engineer role focuses on building and evolving data systems for both internal analytics and customer-facing platforms at Worldly. You'll design scalable cloud-based solutions that integrate generative AI to drive innovation, while developing a data lake to complement their existing data warehouse. This role is impactful because you'll directly contribute to enhancing how businesses understand and improve their supply chain sustainability through advanced data infrastructure.

💡 A Day in the Life

A typical day might involve designing and implementing scalable data solutions using AWS services, developing Python-based data pipelines, and working on DBT transformations to support analytics needs. You could be collaborating with teams to integrate generative AI capabilities into the data platform while ensuring the reliability and performance of both internal and customer-facing analytics systems.

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🎯 Who Worldly Is Looking For

  • Has 5+ years specifically in data engineering with demonstrated experience building AWS ingestion/ETL workflows and working with Postgres databases
  • Possesses advanced SQL expertise combined with strong Python skills for data pipelines, automation, and operational tooling
  • Has hands-on experience with DBT transformations and operational workflows in production environments
  • Shows practical experience or strong interest in integrating generative AI and machine learning into data platforms

📝 Tips for Applying to Worldly

1

Highlight specific AWS services you've used for ingestion/ETL workflows (like Glue, Lambda, Step Functions, or Kinesis) rather than just listing 'AWS experience'

2

Include concrete examples of DBT transformations you've developed and supported in production environments

3

Demonstrate how you've applied Python beyond basic scripting to data pipelines, automation, or operational tooling

4

Showcase any experience with data lakes or lakehouse architectures, especially how they complement traditional data warehouses

5

Mention any sustainability, ESG, or supply chain data experience, even if tangential, to show alignment with Worldly's mission

✉️ What to Emphasize in Your Cover Letter

['Explain how your experience with AWS ingestion/ETL workflows specifically applies to building scalable data platforms', 'Describe your approach to integrating generative AI into data solutions and provide a brief example from your experience', "Connect your skills in DBT transformations and Postgres to how they would enhance Worldly's analytics capabilities", "Express genuine interest in Worldly's mission of providing impact intelligence for supply chain sustainability"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Explore Worldly's impact intelligence platform and understand what specific supply chain data they provide to businesses
  • → Research the ESG (Environmental, Social, Governance) data market and Worldly's position within it
  • → Look into Worldly's existing data infrastructure through any technical blog posts, case studies, or engineering team information
  • → Understand the sustainability challenges in global supply chains that Worldly's data helps address

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk me through how you would design a data lake to complement an existing data warehouse for greater analytics flexibility
2 Describe a specific AWS ingestion/ETL workflow you've built and the challenges you overcame
3 How have you integrated generative AI into data solutions, and what business value did it create?
4 Explain your experience with DBT transformations in production environments and how you ensure reliability
5 How would you approach building systems that support both internal analytics and customer-facing analytics platforms?
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⚠️ Common Mistakes to Avoid

  • Listing generic AWS experience without specifying which services you've used for data ingestion/ETL workflows
  • Claiming DBT experience without being able to discuss specific transformations or operational workflows you've supported
  • Focusing only on data warehouse experience without showing understanding of how data lakes complement warehouses for analytics flexibility

📅 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 Worldly!

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