The Robert Toigo Foundation

Sustainable Finance Data Engineer

Morgan Stanley
Published
May 3, 2022
Location
1585 Broadway, New York, New York
Category
Job Type
City
New York
State
  • New York

Description

This is an Associate level position. The person hired will support the team's activities with a particular focus on our expanding efforts in geospatial, high-frequency and distributed ledger data and analytics. This person will have a dual passion for sustainability and technology, as well as demonstrated expertise in data engineering and distributed systems.

Company Profile:
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 in 43 countries. 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.

Department Profile:
Morgan Stanley's Global Sustainable Finance Group ("GSF") aims to drive the growth of sustainable investing through ongoing development of products and solutions, thought leadership and capacity building initiatives. The GSF team is seeking a quantitative-minded Digital Product Manager to support the team's incubation and execution of innovative digital sustainable finance applications and services for clients of Morgan Stanley. GSF works closely with partners across Morgan Stanley Wealth Management, Investment Management, Institutional Securities Group and Firm Risk Management.

Job Summary:
The Global Sustainable Finance Group (GSF) aims to drive the growth of sustainable investing through ongoing development of products and solutions, economic analysis, thought leadership and capacity building initiatives. The GSF team is seeking a Data Engineer to support the team's activities, with a particular focus on the team's expanding efforts in geospatial, high-frequency and distributed ledger data and analytics. Successful candidates will have a dual passion for sustainability and technology, as well as demonstrated expertise in data engineering and distributed systems. Additionally, successful candidates will be well-organized and detail oriented, and will work well in a collaborative team environment.

Please apply on Taleo HERE.

Responsibilities:

  • Working with GSF data team and various internal partners to maintain the existing infrastructure for ingesting, fusing, and distributing sustainability data.
  • Working alongside cross-functional/firm-wide business and technology teams to design and implement solutions to further the integration of sustainability considerations into investment processes across various asset classes.
  • Collaborating with the data infrastructure team to build tools and processes to rapidly ingest additional sustainability content and ESG data feeds.
  • Ensuring a high standard of data quality and availability with focus on automated testing/regression, monitoring workflows and adjusting processes as needed.
  • Overseeing different data related projects across all phases of development, requirements analysis, application design and implementation.
  • Analyzing and planning implementation of data governance requirements across data sets and entities.

 

Qualifications:

  • Bachelors or Masters in Computer Science, Software Engineering, or a similar field, with strong exposure to data infrastructures.
  • Experience with data engineering, building, deploying and maintaining large, complex data services and pipelines on distributed systems.
  • Fluency in Python and SQL, experience with workflow scheduling tools.
  • Experience maintaining and curating meta-data libraries and Git code repositories and supporting notebook-based data science workflow.

 

Exposure to one or more of the following areas is a plus:

  • Experience implementing machine learning algorithms of prediction and classification.
  • Experience with geospatial data integration, management and processing.
  • Experience in implementing data visualizations in Tableau, Dash or Power BI.
  • Working knowledge of Scala, Java, and/or kdb/Q.

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