Lead Data AI Engineer _Vice President_Data & Analytics Engineering
We’re seeking someone to join our Enterprise Technology as a Lead Data AI Engineer within the Architecture & Modernization team, you will be instrumental in building and maintaining the data infrastructure that powers our technology datalake. This role will involve hands-on development, data pipeline creation, and close collaboration with stakeholders across the organization. You will be one of the first members of the team based in India, providing a unique opportunity to contribute to the team's growth and direction in this location. 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 are also looking for candidates who aspire to contribute to the broader data architecture community and become thought leaders in the space. We value diversity of thought and are committed to building a team that reflects the diversity of our global community.
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. This is a Lead Engineer position at Vice President Level, which is part of the job family responsible for developing and maintains software solutions that support business needs.
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.
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:
- 10+ years of being a practitioner in data engineering or a related field.
- At least 6 years' relevant experience would generally be expected to find the skills required for this role.
- Graduate degree in Computer Science, Information System or equivalent 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 OR Databricks.
- Worked on GenAI projects. Hands-on knowledge of SF Cortex or DBX Genie will be a bonus.
- 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.
Preferred Skills:
- 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.
Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.
Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.
For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.
Skills Required
- 10+ years of practitioner experience in data engineering or a related field
- At least 6 years of relevant experience
- Graduate degree in Computer Science, Information Systems, or an equivalent field
- Proficiency in Python
- Experience with Apache Spark or Hadoop
- Knowledge of SQL and NoSQL database systems
- Experience with Snowflake or Databricks
- Experience working on GenAI projects
- Familiarity with 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 such as Kafka
- Experience with version control systems such as 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
- Hands-on knowledge of SF Cortex or DBX Genie
- Familiarity with Tableau or Power BI
- Familiarity with data governance and security best practices, including data access control and masking
- Experience with Agile methodologies
- Familiarity with data catalog and metadata management tools such as Collibra
- Familiarity with CI/CD pipelines and DevOps practices
Morgan Stanley Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Morgan Stanley and has not been reviewed or approved by Morgan Stanley.
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Parental & Family Support — Family support is extensive, with paid parental leave for all parents, adoption and fertility assistance, backup childcare, and eldercare resources. Feedback suggests these programs meaningfully enhance the overall package and help with retention.
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Healthcare Strength — Health coverage spans medical, dental, vision, mental‑health access, care navigation, and expert second opinions. Convenient primary care access and condition‑specific support reinforce the depth of healthcare coverage.
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Equity Value & Accessibility — Equity compensation and stock ownership are positioned as core motivators that encourage commitment and retention. Feedback suggests education and support are provided to help participants manage equity and related financial benefits.
Morgan Stanley Insights
What We Do
Morgan Stanley mobilizes capital to help governments, corporations, institutions and individuals around the world achieve their financial goals. For over 85 years, the firm’s reputation for using innovative thinking to solve complex problems has been well earned and rarely matched. A consistent industry leader throughout decades of dramatic change in modern finance, Morgan Stanley will continue to break new ground in advising, serving and providing new opportunities for its clients. Morgan Stanley is committed to maintaining the first-class service and high standard of excellence that have always defined the firm. At its foundation are five core values — putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back — that guide its more than 60,000 employees in 1,200 offices across 41 countries.








