Client Asset Development Engineer null

Who You'll Work With

You will work in our McKinsey Knowledge Center in Gurgaon within the Panorama Financial Institutions Center (PFIC).

PFIC is one of the largest knowledge and analytics teams globally and part of the FIG practice, with ~260 members and a global footprint across 20+ countries, focusing on financial services domains, e.g., Retail banking, Corporate & Investment Banking, Wealth & Asset Management, Fintech and Insurance.

McKinsey Panorama IT is a specialized team that is responsible for data modeling and data processing of various McKinsey assets, drives and implements internal developments and is the product owner of the Panorama Data platform.

What You'll Do

You will be responsible for a range of information gathering, processing and optimization tasks, supporting McKinsey proprietary knowledge efforts, focusing on the global financial industry.

In this role, you will participate in the development of complex ETL processes on our platforms, and in building new solutions using VBA, SQL or other programming languages. You'll collaborate with global research teams in improving and expanding the existing assets and capabilities, and in serving some of the world’s major financial institutions.

As part of a very successful research group, operating globally, you will have the opportunity to work in a challenging business environment internationally, to build your data management and analytical skills, and to expand and deepen your understanding of the financial sector worldwide.

Qualifications

• Bachelor or master’s degree in economics, mathematics, statistics, physics, or a related field
• Strong written and verbal communication skills in English
• Relevant experience in SQL/T-SQL or other relational database
• Professional user of Excel with strong VBA knowledge or any other programming language
• Familiarity with Tableau or other visualization tool is an advantage
• Basic understanding of banking economics
• Strong analytical and problem-solving skills
• Outstanding attention to detail and dedication to data accuracy
• Comfortable with multi-tasking, can work efficiently under pressure and keep tight deadlines