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. They provide impactful corporate intelligence primarily for private equity and investment workflows, making them a leader in alternative data analytics. Working here offers exposure to cutting-edge AI applications in finance with massive, diverse datasets.

About This Role

This Data Engineer role focuses on building and maintaining robust data pipelines to support private equity investment workflows at SESAMm. You'll handle ingestion, transformation, and integration of large-scale financial, ESG, market, and alternative data from diverse sources. The role is impactful because it directly enables data-driven investment decisions through reliable, scalable data infrastructure.

💡 A Day in the Life

A typical day involves designing or optimizing data pipelines for ingesting financial and alternative data, collaborating with data scientists to operationalize AI models for investment insights, and ensuring data quality and reliability across the analytics platform. You might also automate workflows, implement CI/CD processes, and work with investment teams to enable efficient data access for time-sensitive decisions.

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Interview Prep

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🎯 Who SESAMm Is Looking For

  • Has 3-5 years experience designing large-scale data pipelines specifically with financial or complex structured/unstructured data
  • Possesses a Master's in Data Engineering, Computer Science, or related field with hands-on technical expertise
  • Has direct experience collaborating in finance, consulting, or private equity environments (not just general tech)
  • Demonstrates advanced proficiency in Python and relevant data engineering tools for scalability and automation

📝 Tips for Applying to SESAMm

1

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

2

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

3

Mention any experience with AI/ML operationalization or collaboration with data science teams in investment contexts

4

Research SESAMm's specific data sources (20B+ articles) and mention how you'd approach ingesting/processing such unstructured data

5

Tailor your resume to emphasize private equity/finance domain experience alongside technical data engineering skills

✉️ What to Emphasize in Your Cover Letter

["Your experience with financial data (ESG, market, alternative) and how it aligns with SESAMm's focus", 'Specific examples of building scalable data infrastructure for investment decision-making workflows', 'Collaboration experience with investment professionals or data scientists in finance environments', "How you've ensured data quality, security, and governance in regulated or sensitive financial data contexts"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → SESAMm's specific AI-driven analytics products and how they serve private equity clients
  • → The types of alternative data sources they use (beyond the 20B+ articles mentioned)
  • → Their technology stack mentions or case studies (look for tools/platforms they might use)
  • → Recent news about SESAMm's growth, funding, or client base in the Toronto/Canadian market

💬 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 unstructured financial news/articles at scale?
2 Describe your experience optimizing data flow performance and reliability for time-sensitive investment data
3 How have you collaborated with investment teams to operationalize analytics in previous roles?
4 What approaches have you used for data versioning and reproducibility in AI/analytics platforms?
5 How do you ensure compliance with security and privacy standards when handling sensitive financial data?
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⚠️ Common Mistakes to Avoid

  • Applying with only generic data engineering experience without finance/private equity domain knowledge
  • Failing to demonstrate specific experience with large-scale, diverse datasets (not just clean, structured data)
  • Not showing understanding of investment workflows or how data engineering supports decision-making in finance

📅 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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