Data Science Engineer

SESAMm ( extracts behavioral insights from millions of unstructured text data sources across the public internet in over 100 languages, helping clients distill valuable intelligence on businesses and their customers to make investment decisions and manage risk.
We work with many well-known firms around the world in private equity, investment banking, insurance, and asset management to apply Natural Language Processing and Artificial Intelligence algorithms to track e-reputation, competitive positioning, sentiment analysis, risk and ESG factors.
SESAMm is growing quickly, with over 90 team members around the globe and offices in Paris, New York, London, Metz, Tunis, and Tokyo.
Alternative Data, Natural Language Processing, Machine Learning and Quantitative Analysis.
The Data Engineer Role
SESAMm, in partnership with one of the largest private equity (PE) firms in the United States, is seeking a data engineer to join an exciting AI platform project designed to transform investment analysis. This project is at the cutting edge of private equity, leveraging advanced artificial intelligence (AI) to improve data-driven decision-making. As a data engineer, you will contribute to a groundbreaking platform used by deal teams to accelerate and enhance due diligence.
Data Architecture & Pipeline Development: Design, build, and maintain robust data pipelines and architectures to support private equity investment workflows. Ensure seamless ingestion, transformation, and integration of large, diverse datasets (financial, ESG, market, and alternative data) from multiple internal and external sources
Develop scalable data infrastructure, monitor and optimize data flow performance, reliability, and data quality. Collaboration with Data Science & Investment Teams: Partner with data scientists, investment professionals, and operations teams to operationalize analytics. Enable efficient data access, versioning, and reproducibility across the AI and analytics platform.
Automate data workflows, implement CI/CD pipelines, and contribute to the continuous improvement of data engineering practices. Master's degree in Data Engineering, Computer Science, or a related technical field.

3-5 years of hands-on experience designing and maintaining large-scale data pipelines.

• Proven experience working with structured and unstructured financial data or other complex data domains.
• Advanced proficiency in Python and SQL for data processing and transformation.

Hands-on experience with cloud data platforms (e.g. AWS, Azure, GCP, or Databricks) and data workflow orchestration tools (e.g. Strong understanding of data modeling, schema design, and API integration.
Experience with big data frameworks (Spark, Kafka, Delta Lake, etc.) Familiarity with version control (Git) and DevOps practices (CI/CD pipelines).
Fluency in English; French is a plus.
SESAMm is growing rapidly, creating ongoing opportunities for personal and professional growth. Professional Development : Work alongside industry-leading experts and gain valuable exposure to advanced AI and ML technologies applied in private equity. This role offers a unique opportunity to deepen your expertise in these cutting-edge applications.
Mentorship & Training : SESAMm provides structured training and mentorship, with a strong emphasis on knowledge-sharing. Internally and externally led training sessions are organized, and we offer access to educational platforms, encouraging you to expand your AI skill set.
Global Perspective : Collaborate with teams based across Europe and the United States, gaining hands-on international experience in a fast-paced, high-impact environment. This global perspective helps broaden your skill set and provides insights into international market dynamics.
We focus on being a learning organization that values and supports teamwork, thoughtfulness, and work/life balance.