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Morgan Stanley

Data AI Engineer, Dir, P4

Posted 2 Days Ago
Be an Early Applicant
In-Office
New York, NY, USA
150K-190K Annually
Senior level
In-Office
New York, NY, USA
150K-190K Annually
Senior level
The Data AI Engineer will develop data infrastructure and pipelines, implement governance, optimize systems, and collaborate with stakeholders to enhance AI capabilities at Morgan Stanley.
The summary above was generated by AI

Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities.
Our mission is to develop a firmwide Artificial Intelligence (AI) Development Platform that aligns with the firm's Technology principles and drives efficiency and consistency, controls, security and strong governance and promotes innovation, enabling teams to build applications that leverage AI capabilities and accelerate the adoption of AI across our businesses.

Position Overview
As a Data AI Engineering Specialist within the Architecture & Modernization team, you will be instrumental in building and maintaining the data infrastructure for our Data AI platforms. This role will involve hands-on development, data pipeline creation, and close collaboration with stakeholders across the organization. This role requires a self-starter with strong execution skills and the ability to work independently. You will be expected to not only execute on the current strategy but also contribute to its evolution. We value diversity of thought and are committed to building a team that reflects the diversity of our global community.

This is a hybrid position requiring a minimum of three days per week in the office. The role is based in NYC, and may also be based in Montreal for qualified candidates in Canada.

What you'll do in the role

  • Develop and maintain data pipelines and ETL (Extract, Transform, Load) processes.
  • Work with structured and unstructured data to ensure it is accessible and usable.
  • Optimize data systems for performance and scalability.
  • Implement data quality and data governance standards.
  • Collaborate with stakeholders across technology and business units to understand their data needs and translate them into technical solutions and provide data-driven insights.
  • Contribute to the documentation and knowledge sharing within the team, creating, and maintaining technical documentation and training materials.
  • Participate in code reviews and contribute to the improvement of development processes.
  • Contribute to the broader data architecture community through knowledge sharing, presentations.

What you'll bring to the role

  • 8 years+ of being a practitioner in data engineering or a related field.
  • Proficiency in programming skills in Python
  • Experience with data processing frameworks like Apache Spark or Hadoop.
  • Knowledge of database systems (SQL and NoSQL).
  • Experience working on Snowflake and Databricks.
  • Experience on Snowflake Cortex will be really appreciated.
  • Familiarity with cloud platforms (AWS, Azure) and their data services.
  • Understanding of data modeling and data architecture principles.
  • Experience with data warehousing concepts and technologies.
  • Experience with message queues and streaming platforms (e.g., Kafka).
  • Experience with version control systems (e.g., Git).
  • Experience using Jupyter notebooks for data exploration, analysis, and visualization.
  • Excellent communication and collaboration skills.
  • Ability to work independently and as part of a geographically distributed team.

Nice to have

  • Familiarity with data visualization tools (e.g., Tableau, Power BI).
  • Familiarity with data governance and security best practices (e.g., data access control, data masking).
  • Experience with Agile methodologies.
  • Familiarity with data catalog and metadata management tools (e.g., Collibra).
  • Familiarity with CI/CD pipelines and DevOps practices.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 years.  Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There’s also ample opportunity to move about the business for those who show passion and grit in their work.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices​ into your browser.

Expected base pay rates for the role will be between $150,000 to $190,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs. 

Morgan Stanley's goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our standards of integrity and excellence. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees.

It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.

Morgan Stanley is an equal opportunity employer committed to diversifying its workforce (M/F/Disability/Vet).

Top Skills

Spark
AWS
Azure
Databricks
Git
Hadoop
Jupyter
Kafka
NoSQL
Python
Snowflake
SQL
HQ

Morgan Stanley New York, New York, USA Office

1585 Broadway, New York, NY, United States, 10036

Morgan Stanley New York, New York, USA Office

522 5th Ave, New York, NY, United States

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