Why this role stands out
This hybrid internship offers a fantastic opportunity to gain hands-on experience in data engineering within a globally recognized, sustainable wealth management firm, allowing you to directly impact data delivery optimization. You'll thrive here if you're a Master's student eager to analyze complex data patterns and collaborate with stakeholders to drive efficiency in a reputable, forward-thinking organization. Apply now to develop valuable skills and contribute to a legacy of innovation.
Quick overview
Job description
An innovative bank of choice for private and institutional clients, our independently owned Firm is one of the best-capitalised banking groups in the world, managing close to CHF 300 billion and operating from over 25 offices across 4 continents. With a history spanning over 230 years,
Lombard Odier is an investment house providing a comprehensive offering of discretionary and advisory portfolio management, wealth services and custody.
We also offer asset management services and investment strategies through
Lombard Odier Investment Managers and provide advanced banking technology to other financial institutions.
“Rethink Everything” is our philosophy
– it is at the heart of everything we do. Internship – Data Engineer - Optimization of Data Delivery
Modern organizations depend on fast, reliable and secure access to high-quality data. This internship focuses on understanding how data is consumed across the organization and helping define a future-state operating model for data distribution.
Analyse current data consumption patterns and propose improvements that increase efficiency, consistency and scalability across the bank. Master's student in Data Engineering, Computer Science or Information Systems. Cross-functional interactions with business and IT teams. We firmly believe that building Diverse Teams contributes to our successes and to deliver on this, we actively embed Diversity, Equity and Inclusion in our business strategy. It is an exciting time to join our Teams.
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