Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management, and wealth management services. The Firm's employees serve clients worldwide including corporations, governments and individuals from more than 1,200 offices. As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic. Morgan Stanley can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.
Technology works as a strategic partner with Morgan Stanley business units and the world's leading technology companies to redefine how we do business in ever more global, complex, and dynamic financial markets. Morgan Stanley's sizeable investment in technology results in quantitative trading systems, cutting-edge modeling and simulation software, comprehensive risk and security systems, and robust client-relationship capabilities, plus the worldwide infrastructure that forms the backbone of these systems and tools. Our insights, our applications and infrastructure give a competitive edge to clients' businesses and to our own.
Morgan Stanley Enterprise Technology Service is looking for a data engineer to join our Data Service & Analytics team. The Data Engineer will support our data analysts and data scientist, ML engineer by working on analytics and ML projects as well creating fundamental component to support wider user communities across line of business in Morgan Stanley. The candidate must be self-motivated, dedicated, accountable and able to identify issue and find solutions independently.
- Support our existing big data platform.
- Expand and enhance our data pipeline.
- Design, build and support our analytics and AI/ML platform and ML pipeline on cloud.
- Support AL/ML operation on ML governance, process and release management.
- Identify process improvement opportunities, automate manual processes and optimize data delivery.
- Create prototyping for analytics and AI/ML tools
- Support user communities to build applications on the platforms the team build.
- Working experience on big data platform such as Hadoop, Databricks, etc.
- Working experience with Cloud platform such as AWS and Azure.
- Working coding experience on programming languages such as Python and Java.
- Understanding of data analysis techniques and procedures
- Understanding of machine learning process and operation
- Understand security principal and practice on cloud platforms
- Understand data governance and ML governance principals
- Strong communication and organization skills.
- Bachelor's degree in Computer Science or related fields required, Master's desired
- Working experience on ETL tools such as AWS Glue ETL or Databricks
- Working experience on AWS Glue and SageMaker
- Working experience with tools used by Data Scientist
- Working experience on network and security related areas
- 3 years of experience on data engineering, ml engineering or ml operation engineering
Sep 19, 2022
Americas-United States of America-Georgia-Alpharetta