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Job Overview



Job Role

Investment Banking

Gender preferred

No Preferences

Work preferred

Work from Office



Any Graduation

Post Graduation

Any Post Graduation


Vice President - Cloud Data & Analytics Engineer

Job Number:


POSTING DATE: Sep 21, 2022

PRIMARY LOCATION: Non-Japan Asia-India-Karnataka-Bengaluru

EDUCATION LEVEL: Bachelor's Degree

JOB: Development


JOB LEVEL: Vice President


Vice President - Cloud Data & Analytics Engineer - Investment Management IT

Company Profile

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, wealth management and investment management services. With offices in more than 41 countries, the Firm's employees serve clients worldwide including corporations, governments, institutions and individuals. For further information about Morgan Stanley, please visit

Investment Mangement IT (IMIT)

IMIT provides industry-leading strategies and solutions to enable business growth and deliver “best in class” functions to Morgan Stanley’s Investment Management business.

Job Profile

The position is for a Cloud Data & Analytics Engineer within the Data Strategy team at MSIM. The candidate is expected to work on design and development of end to end Cloud based solutions with heavy focus on analytics and data, with good understanding of underlying cloud infrastructure

Skill Set: Data Engineering / Python / Spark / Cloud

Primary skills

Independently lead & manage execution of data engineering projects

Engineer complete technical solutions to solve concrete business challenges in the areas of Data management, Business Intelligence and self-service analytics

Collect functional and non-functional requirements, consider technical environments, business constraints and enterprise organizations

Support our clients in executing their Big Data strategies by designing and building operational data platforms: ETL pipelines, data anonymization pipelines, data lakes, near real-time streaming data hubs, web services, training and scoring machine learning models.

Troubleshoot and quality check work done by team members

Collaborate closely with partners, strategy consultants and data scientists in a flat and agile organization where personal initiative is highly valued

Share data engineering knowledge by giving technical trainings

Communicate and interact with clients at the executive level

Guide and mentor team members

The candidates should have strong capabilities in data engineering along with a proven expertise in team management.

Candidates should also be proficient in project and senior stakeholder management.

A broad practice in multiple software engineering fields

Experience on managing & leading data engineering / warehousing projects

Must have experience on Python, SQL and Distributed programming languages, preferable Spark

Experience working on Cloud, Azure is a plus

Experience working setting up data lakes using entire Big Data and DWH ecosystem

Experience on data workflows and ETL, Apache Airflow is a plus

Comfortable with Unix OS type systems, Bash and Linux


Skill Set

Required Experience: 10 - 15 years

Skill Set: Python / Data Engineering / Spark / Machine Learning

  • Primary skills

Strong interpersonal skills and team spirit is required in addition to proficiency in verbal and written business communications. We support what we build - individual will be responsible for post-production support on a rotation basis.

Experience with Python /Spark

Expert-level core Python knowledge in a UNIX/Linux environment; minimum 3 years

Experience developing & designing complex, data-driven systems in Python, ideally with a Web / HTML5 component

Expertise with Python and UI components used in a production environment

Experience with automated testing frameworks

Strong enthusiasm for code quality, and desire to build long-standing and stable systems

Strong communication skills, both technical and otherwise, that can be leveraged to collaborate with a diverse set of stakeholders

Numpy / pandas / Plotly / Flask/ Jupyter/Backtesting libraries and general data science stack

Experience thorough understanding of programming fundamentals such as OOP, Data Structures and Algorithm Design

  • Good to have skills

Experience with Azure ADF, Databricks, Enterprise Dash

Experience with Spark, Spark Streaming, Kafka, MLLib

Experience with Docker, Kubernetes


Preferred Qualifications: Bachelor's Degree with 10 to 15 years of experience in related field



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