Application Guide

How to Apply for Fullstack Engineer (Semantic / Analytics) (m/f/d)

at Integrity Next

🏢 About Integrity Next

Integrity Next is dedicated to enhancing corporate supply chains for a more sustainable world, making it a mission-driven company for those passionate about sustainability. By leveraging data and analytics, they empower businesses to make ethical and environmentally conscious decisions. Working here means contributing to a meaningful cause while being part of a tech-forward, remote-first team.

About This Role

This Fullstack Engineer role focuses on building and evolving the semantic layer in dbt and Snowflake, defining KPIs and business logic, and exposing curated data for BI tools, APIs, and AI consumption. You'll collaborate cross-functionally to ensure data models reflect fresh, reliable data, directly impacting how sustainability insights are derived and used. Your work will be critical in enabling data-driven decisions for a more sustainable supply chain.

💡 A Day in the Life

A typical day might start with a stand-up with the data platform team to discuss progress on semantic models. You'll then dive into dbt to define new metrics or refine existing ones, collaborate with product managers on KPI definitions, and later write Python APIs to expose curated data. You might also pair with AI engineers to ensure semantic models are optimized for Snowflake Cortex AI consumption.

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Interview Prep

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🎯 Who Integrity Next Is Looking For

  • Expert in SQL and data modeling, with proven experience in Snowflake semantic views and dbt at scale.
  • Skilled in Python and API development (REST or GraphQL), with solid AWS stack knowledge.
  • Experienced in building semantic layers, reusable metrics, and canonical data models, with a strong analytics engineering mindset.
  • Collaborative and able to work with business and product stakeholders to define KPIs and semantic consistency standards.

📝 Tips for Applying to Integrity Next

1

Highlight specific projects where you built semantic layers or reusable data models using dbt and Snowflake.

2

Showcase your experience with Snowflake Cortex AI or similar AI/ML integrations, as the role mentions AI consumption.

3

Demonstrate your Python and API development skills with concrete examples of REST or GraphQL APIs you've built.

4

Mention any experience with BI tools like Amazon QuickSight or Apache Superset, as the role involves exposing data to them.

5

Tailor your cover letter to emphasize your passion for sustainability and how your technical skills can drive Integrity Next's mission.

✉️ What to Emphasize in Your Cover Letter

['Your strong hands-on experience with Snowflake and dbt at scale.', 'Your ability to define KPIs and business logic collaboratively with non-technical stakeholders.', 'Your experience building APIs and working with AWS stack, as required for exposing data.', 'Your enthusiasm for using data to drive sustainability in supply chains.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Understand Integrity Next's current sustainability initiatives and how they measure supply chain impact.
  • → Familiarize yourself with Snowflake Cortex AI capabilities, as the role mentions AI consumption.
  • → Look into the company's tech stack blog or engineering culture to understand their dbt and Snowflake usage patterns.
  • → Review any public case studies or whitepapers on how they use data to enhance supply chain sustainability.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk through a past project where you built a semantic layer: challenges, design decisions, and outcomes.
2 How would you design a reusable metric for carbon footprint across different business units?
3 Explain how you would expose data for both BI tools and AI consumption using Snowflake and dbt.
4 How do you ensure data freshness and reliability in semantic models when working with multiple operational systems?
5 Describe your experience with Snowflake Cortex AI or similar AI features; how would you leverage them for this role?
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⚠️ Common Mistakes to Avoid

  • Downplaying the importance of semantic consistency and canonical data models—this is core to the role.
  • Focusing only on backend skills without showing understanding of analytics engineering and stakeholder collaboration.
  • Not demonstrating experience with both dbt and Snowflake semantic views—mentioning only one is insufficient.

📅 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 Integrity Next!

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