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Job Overview

Category

CA, CFA, CMA, MBA, MCOM/BCOM, CS

Job Role

Investment Banking

Gender preferred

No Preferences

Work preferred

Work from Office

Qualification

Graduation

Any Graduation

Post Graduation

Any Post Graduation

Description




Vice President - Cloud Data & Analytics Engineer








Job Number:


3224309




POSTING DATE: Sep 21, 2022


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


EDUCATION LEVEL: Bachelor's Degree


JOB: Development


EMPLOYMENT TYPE: Full Time


JOB LEVEL: Vice President






DESCRIPTION









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 www.morganstanley.com.












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





















QUALIFICATIONS









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















Qualifications/Criterion










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









Skills

AnalyticsStrategyPython

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