Ready to take the next step in your career and make your mark in the financial world?
At Vontobel, we believe diverse perspectives drive innovation and success. That’s why we’re excited to welcome passionate, ambitious, and curious students into our Early Careers Internship Program. Whether you’re fascinated by finance, technology or investments, this program offers you the chance to collaborate with a dynamic team, receive personalized support, and contribute to projects that truly matter.
Over 6 months, starting on 1 March 2027, you’ll gain hands-on experience and insights into the financial industry while building lasting connections in a globally recognized investment firm.
What would your role be?
We are looking for a motivated, analytical, and autonomous Quant Data Engineer Intern who can bridge the gap between financial data and institutional-grade infrastructure. While our core expertise lies in deep fundamental market analysis and investment strategies, we process vast amounts of quantitative data daily. We trade a variety of financial indices composed of commodity futures and are now looking to elevate our data infrastructure to the next level. As fundamental portfolio managers, we will provide financial insights, portfolio models, and the requirements for the output. Your mission is to build the backend, the data pipelines, and the front-end. You will design a robust, fully automated system that handles everything from daily data ingestion to advanced portfolio analytics and interactive visualization.
Build the Data Infrastructure: Design and implement a fully automated pipeline to ingest daily index position files, alongside futures price feeds from premium financial vendors (e.g., Bloomberg, Datastream) into our Snowflake database.
Ensure Institutional Stability (DataOps): Create a bulletproof daily process. This includes building automated monitoring tools, error handling, holiday calendars, and data-integrity checks to ensure no file is missed or corrupted.
Implement Portfolio Analytics: Translate our financial concepts into Python code. You will implement various portfolio construction methodologies, factor models, risk/return look-through metrics, and contribution analysis.
Develop a High-End Digital Dashboard: Build an interactive, crisp digital dashboard (e.g., using Streamlit, or similar) allowing us to "slice and dice" index data, look-through allocations, factor exposures, and risk metrics across multiple layers.
What are we looking for?
Education: Advanced student (Master/PhD) or recent graduate in Computer Science, Physics, Data Science, Mathematics, Quantitative Finance, or a related field.
Software Engineering & Data Pipelines: Strong Python proficiency with the ability to write clean, modular, and production-ready code. Experience with automation, cron-jobs/orchestration, and Git version control.
Database & Cloud Architecture: Solid expertise in SQL and hands-on experience setting up/managing cloud data warehouses (specifically Snowflake or Azure/AWS architectures).
Frontend & Visualization: First experience building clean, interactive web applications/dashboards for data analytics (e.g., Python Streamlit, Plotly Dash, Shiny).
Mindset: A high degree of autonomy. You enjoy taking a business requirement and figuring out the technical architecture to solve it independently.
Finance Interest: Strong interest in commodity markets, financial indices, and derivative/futures markets. (Prior knowledge of portfolio construction or risk factors is a big plus, but not mandatory).
What you bring
We are seeking highly motivated students that share our values :
Ownership : You are curious and get involved. You ask why a process works the way it does, offer to help where your team needs it, and see your own projects through from start to finish.
Tenacity : You are driven and self-dependent. When the data doesn’t add up or the first approach fails, you look for another way and you come back with an answer.
Foresight…