Application Guide

How to Apply for Data Engineer

at SESAMm

🏢 About SESAMm

SESAMm is a specialized AI analytics company that processes over 20 billion articles to extract ESG, sentiment, and thematic insights for corporate clients, particularly in private equity. Their unique value lies in transforming massive unstructured text data into actionable investment intelligence, making them a leader in alternative data analytics for finance. Working here offers exposure to cutting-edge NLP and data engineering challenges at the intersection of finance and AI.

About This Role

This Data Engineer role focuses on building and maintaining data pipelines that ingest, transform, and integrate diverse financial, ESG, and alternative datasets to support private equity investment decisions. You'll ensure scalability, reliability, and data quality while collaborating closely with data scientists and investment teams to operationalize analytics. The impact lies in enabling data-driven investment strategies through robust infrastructure that handles billions of articles and complex financial data.

💡 A Day in the Life

A typical day involves optimizing data pipelines that ingest and process billions of articles for ESG and sentiment analysis, collaborating with data scientists to refine models for investment insights, and ensuring data quality and compliance across financial datasets. You might automate workflows, troubleshoot pipeline performance issues, and design scalable architectures to support private equity teams' data needs.

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🎯 Who SESAMm Is Looking For

  • Has 3-5 years of experience designing large-scale data pipelines specifically with structured/unstructured financial data (e.g., market data, ESG metrics, news articles)
  • Possesses a Master's in Data Engineering/Computer Science and advanced Python skills, with proven ability to work in finance, consulting, or private equity environments
  • Demonstrates experience optimizing data flow performance and reliability while ensuring compliance with security and governance standards in financial contexts
  • Shows collaborative experience with data science teams to operationalize analytics and enable reproducible data access for AI platforms

📝 Tips for Applying to SESAMm

1

Highlight specific projects where you processed financial or alternative data (ESG, sentiment, market data) at scale, quantifying pipeline performance metrics

2

Emphasize experience with data governance, security, and privacy standards relevant to financial data handling in European/FR contexts

3

Detail collaboration examples with investment professionals or data scientists to translate analytics into operational workflows

4

Showcase automation of data workflows and CI/CD implementation in finance-related environments

5

Tailor your resume to mention tools/architectures for handling unstructured text data (like news articles) alongside structured financial data

✉️ What to Emphasize in Your Cover Letter

["Your hands-on experience with financial/alternative data pipelines and how it aligns with SESAMm's focus on ESG and sentiment analytics from billions of articles", 'Specific examples of collaborating with investment or data science teams to operationalize analytics in finance environments', "How you've ensured data quality, scalability, and compliance in previous roles, particularly with sensitive financial data", "Your interest in SESAMm's AI-driven approach to investment insights and how your skills contribute to their private equity workflows"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → SESAMm's specific products and clients in private equity/ESG analytics, including case studies on their website
  • → The types of alternative data they process (beyond articles) and their data sources/partnerships
  • → Their technology stack hints from job posts or tech blogs (look for mentions of Python, cloud platforms, NLP tools)
  • → Recent news about SESAMm's growth, funding, or expansions in the ESG analytics market

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Describe your experience designing data pipelines for unstructured text data (like news/articles) alongside structured financial data
2 How have you ensured data quality and reliability in pipelines handling billions of records for financial decision-making?
3 Explain a time you collaborated with data scientists to productionize analytics models in a finance or private equity context
4 What approaches have you used to optimize data flow performance and scalability while maintaining security/compliance standards?
5 How would you design a pipeline to integrate ESG metrics, market data, and sentiment analysis from articles for investment workflows?
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⚠️ Common Mistakes to Avoid

  • Applying with generic data engineering experience without highlighting financial/alternative data or private equity domain knowledge
  • Failing to demonstrate collaboration with non-technical teams (investment professionals, data scientists) in finance contexts
  • Neglecting to discuss data governance, security, or compliance aspects relevant to handling sensitive financial information

📅 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 SESAMm!

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