Application Guide

How to Apply for Data Engineer (m/f/x)

at Makersite

🏢 About Makersite

Makersite is an AI-driven platform that uniquely accelerates eco-friendly product development for manufacturers 40x faster than traditional methods. Working here means contributing to tangible environmental impact through technology, specifically by helping manufacturers design more sustainable products efficiently. The company's focus on combining data engineering with sustainability goals creates a mission-driven work environment that appeals to engineers wanting purpose beyond just technical challenges.

About This Role

This Data Engineer role involves designing and maintaining scalable data pipelines and infrastructure specifically to support Makersite's analytics and machine learning workflows for eco-friendly product development. You'll be crucial in ensuring data quality and accessibility for the AI platform that accelerates sustainable manufacturing decisions. Your work directly enables the 40x faster product development that differentiates Makersite in the market.

💡 A Day in the Life

A typical day might involve optimizing data pipelines that feed Makersite's AI models for product sustainability analysis, collaborating with data scientists to understand new feature requirements, and implementing data validation processes to ensure quality for client manufacturing data. You'd likely spend time designing scalable storage solutions on AWS while maintaining robust security protocols for sensitive information.

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🎯 Who Makersite Is Looking For

  • Has 5+ years commercial experience with SQL and Python, specifically with 3+ years building data pipelines for analytics/ML workflows
  • Demonstrates hands-on experience with data orchestration tools like Airflow, Metaflow, or Prefect in production environments
  • Possesses strong AWS expertise (Azure is a plus) with experience designing scalable data storage solutions for performance and reliability
  • Understands data compliance and security best practices, particularly relevant when handling sensitive client manufacturing data

📝 Tips for Applying to Makersite

1

Highlight specific experience with data pipelines supporting machine learning workflows, not just traditional ETL

2

Quantify your impact with metrics related to pipeline performance, data quality improvements, or scalability achievements

3

Mention any experience with sustainability, manufacturing, or environmental data domains to show domain relevance

4

Explicitly list your AWS services expertise (e.g., Redshift, Glue, S3, Lambda) and orchestration tool experience

5

Include examples of collaborating with data scientists/analysts to translate business needs into technical solutions

✉️ What to Emphasize in Your Cover Letter

["Explain why you're specifically interested in Makersite's mission of accelerating sustainable product development", 'Provide concrete examples of building scalable data pipelines that supported analytics or ML workflows', 'Describe your experience ensuring data quality and compliance, particularly with sensitive client data', 'Highlight your collaboration experience with data scientists/analysts to solve business problems']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Explore Makersite's platform and case studies to understand how their AI accelerates sustainable product development
  • → Research the manufacturing sustainability challenges Makersite addresses to understand the business context
  • → Look into the company's technology blog or announcements to understand their current tech stack direction
  • → Understand the regulatory environment around manufacturing data in the EU, given the remote EU requirement

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk through your experience designing a scalable data pipeline from ingestion to consumption for analytics/ML
2 How have you ensured data quality and consistency in previous roles, especially with sensitive data?
3 Describe a time you collaborated with data scientists to understand their data needs and built solutions accordingly
4 What AWS services have you used for data storage and processing, and how did you optimize for performance/cost?
5 How do you approach data compliance and security when working with client data in cloud environments?
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⚠️ Common Mistakes to Avoid

  • Applying with only database administration or traditional ETL experience without ML/Analytics pipeline background
  • Failing to demonstrate specific AWS expertise beyond basic familiarity
  • Not showing understanding of data compliance/security considerations for sensitive client data

📅 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!

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Good luck with your application to Makersite!

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