Data Analytics lead for Global Credit
- The role of Data Analytics lead for Global Credit, responsible for defining and implementing a roadmap for Data, Cloud and Analytics capabilities including Data Warehousing, Real Time analytics and reporting.
- This role sits with in the Credit Architecture and Engineering Technology Team. The Credit Architecture and Engineering Team is responsible for building technology solutions for trading of Corporate Bonds and Credit Derivatives, Loans and Risk.
- Credit Markets are experiencing significant change due to changing client needs, competitors, and technology, crafting an exciting opportunity to partner with the business to build next generation Data Analytical capabilities to support Sales, Trading and Risk management. This multi-year investment program includes the development of a new Data Analytics platform for Credit products.
- The primary responsibilities of the Data Analytics lead for Global Credit include:
a. Define Business, Functional, and Non-Functional Requirements for Data Platform
b. Define target state architecture, design and lead the implementation of the Data Platform, lead the data governance effort.
c. Partner with Credit Sales and Trading leaders in both NY and London to prioritize new capabilities and define a delivery roadmap.
d. Work with the Development, Testing, and Deployment teams to understand and implement data and analytical capabilities.
e. Drive adoption of the Cloud and the PAS capabilities. Develop concrete roadmap and the implementation plan to migrate of the existing on-prem solution to Azure
f. Lead the hiring effort to build the team of the data engineers and data scientists to work on the platform You Offer
- At least 5-10 years' experience crafting and implementing Data Strategy at a major financial institution.
- Proficient with crafting and implementation of the complex Data Warehousing, Data Lakes and Big Data solutions!
- Hands on expertise with Hadoop and Spark
- Hands on experience with Big Data cloud implementations on AWS, GCP or Azure
- Experience in crafting ML and AI solutions
- Should have experience defining a technology tool that has been built from the ground up.
- Experience writing business requirements and functional requirements documentation
- Experience in balancing distributed team