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Morgan Stanley

Manages investments and advises on financing

Lead Data AI Engineer Vice President Data & Analytics Engineering

Data EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 10 years of practitioner experience in data engineering or a related field.
  • A graduate degree in Computer Science, Information Systems, or an equivalent field.
  • Proficiency in Python programming.
  • Experience with data processing frameworks such as Apache Spark or Hadoop.
  • Knowledge of SQL and NoSQL database systems.
  • Experience working with Snowflake or Databricks.
  • Experience working on generative AI projects.
  • Familiarity with cloud platforms such as AWS or 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.
  • Ability to work independently and as part of a geographically distributed team.

Responsibilities

  • Develop and maintain data pipelines and extract, transform, and load (ETL) 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 technology and business stakeholders to understand data needs, translate them into technical solutions, and provide data-driven insights.
  • Create and maintain technical documentation and training materials, and contribute to team knowledge sharing.
  • Participate in code reviews and contribute to improving development processes.
  • Contribute to the broader data architecture community through knowledge sharing and presentations.

Desired Qualifications

  • Hands-on knowledge of Snowflake Cortex or Databricks Genie.
  • Familiarity with data visualization tools such as Tableau or Power BI.
  • Familiarity with data governance and security best practices, including data access control and data masking.
  • Experience with Agile methodologies.
  • Familiarity with data catalog and metadata management tools such as Collibra.
  • Familiarity with continuous integration and continuous delivery (CI/CD) pipelines and DevOps practices.

About the Company

Morgan Stanley

Manages investments and advises on financing

Morgan Stanley advises companies and governments on financing and manages investments for institutions, individuals, and families. Its business combines investment banking and securities trading with wealth management and an asset-management division that invests across public and private markets. Bankers arrange stock and bond sales and advise on mergers, while advisors build client portfolios and fund managers invest money under agreed strategies. The firm earns advisory and management fees, trading revenue, commissions, and interest from lending and deposits. Morgan Stanley was founded as a partnership in 1935 and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1935

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