Application Guide

How to Apply for Data Engineer

at SESAMm

🏢 About SESAMm

SESAMm is a unique AI-driven analytics company specializing in ESG, sentiment, and thematic insights extracted from over 20 billion articles, providing corporate clients with actionable intelligence. Their focus on alternative data for private equity and investment workflows makes them a leader in applying AI to financial decision-making. Working here offers the chance to build data infrastructure that directly impacts investment strategies using cutting-edge NLP and analytics.

About This Role

This Data Engineer role involves designing and maintaining robust data pipelines specifically for private equity investment workflows, handling diverse datasets including financial, ESG, and alternative data. You'll ensure seamless ingestion and transformation of large-scale data while collaborating with data scientists and investment teams to operationalize analytics. The role is impactful because it directly enables data-driven investment decisions through scalable, reliable data infrastructure.

💡 A Day in the Life

A typical day involves designing and optimizing data pipelines for ingesting financial and alternative data, collaborating with data scientists to operationalize analytics models, and ensuring data quality and reliability for investment teams. You might automate workflows, implement CI/CD processes, and work on scaling infrastructure to handle SESAMm's massive 20+ billion article dataset while maintaining security and governance standards.

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🎯 Who SESAMm Is Looking For

  • Has 3-5 years of hands-on experience building large-scale data pipelines, specifically with structured/unstructured financial data or complex domains
  • Demonstrates proven collaboration experience in finance, consulting, or private equity environments (not just tech companies)
  • Possesses advanced proficiency in Python and relevant data engineering tools for pipeline development and automation
  • Holds a Master's degree in Data Engineering, Computer Science, or related technical field with practical application experience

📝 Tips for Applying to SESAMm

1

Highlight specific experience with financial data pipelines (ESG, market data, alternative data) rather than generic ETL projects

2

Quantify your impact on data pipeline performance, reliability, or scalability in previous finance-related roles

3

Demonstrate understanding of private equity workflows and how data engineering supports investment decisions

4

Showcase experience with both structured and unstructured data processing relevant to SESAMm's 20+ billion article corpus

5

Include examples of collaborating with data scientists and investment professionals, not just technical teams

✉️ What to Emphasize in Your Cover Letter

['Explain how your data engineering experience specifically applies to financial/alternative data processing', 'Describe your understanding of private equity workflows and how data pipelines support investment decisions', 'Highlight experience with data quality, security, and governance in regulated financial environments', "Connect your skills to SESAMm's AI-driven analytics platform and their 20+ billion article data corpus"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Study SESAMm's specific products and how they use alternative data for ESG and sentiment analytics
  • → Understand the private equity investment workflow and how data engineering supports it
  • → Research the types of alternative data sources SESAMm likely uses (news, social media, filings, etc.)
  • → Learn about current trends in ESG investing and how data analytics drives these decisions

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 How would you design a pipeline for ingesting and processing ESG data from multiple external sources?
2 Describe your experience optimizing data flow performance and reliability for financial analytics
3 How have you collaborated with investment teams to operationalize data science models?
4 What approaches have you used for data versioning and reproducibility in analytics platforms?
5 How would you ensure compliance with security and privacy standards when handling financial data?
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⚠️ Common Mistakes to Avoid

  • Presenting generic data engineering experience without financial/alternative data context
  • Failing to demonstrate understanding of private equity or investment workflows
  • Overemphasizing academic credentials without showing practical pipeline development experience

📅 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 SESAMm!

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