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Morgan Stanley
Morgan Stanley

Leading company in the financial services industry

Data modeler - Vice President - Data & Analytics Engineering

RoleFrontend
LevelMid Level
LocationMumbai, India
WorkOn-site
TypeFull-time
Posted3 months ago
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Benefits and perks

Parental Leave

Flexible Hours

Learning Budget

Required skills

React

JavaScript

Node.js

We're seeking someone to join our WM Technology team as a Data modeler, in WM Product Technology to As a Senior Data modeler, the candidate will be a key architect of our Data Landscape, responsible for designing, developing and maintaining robust and scalable data models that support our business objectives. The Data modeler will help translate complex data requirements into logical and physical data designs, ensuring data integrity, consistency, and optimal performance for various Analytical and operational systems
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 Vice President position that provides specialist data analysis and expertise that drive decision-making and business insights as well as crafting data pipelines, implementing data models, optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI-based techniques.
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:

Primary Skills:

  • Database design and Data Modelling experience
  • Strong with SQL with hands-on using Data Modelling tools like Power designer or Erwin. Experience in any one of the Database like Teradata, SQL Server, Hadoop Hive, Snowflake etc
  • Understand and translate business needs into data models supporting strategic solutions.
  • Create and maintain conceptual, logical and physical data models along with corresponding metadata.
  • Develop best practices for standard naming conventions and coding practices to ensure consistency of data models.
  • Recommend opportunities for reuse of data models in new environments.
  • Perform reverse engineering of physical data models from disparate databases and SQL scripts.
  • Evaluate data models and physical databases for variances and discrepancies.
  • Validate business data objects for accuracy and completeness.
  • Analyze data-related system integration challenges and propose appropriate solutions.
  • Develop data models according to company standards.
  • Guide System Analysts, Engineers, Programmers and others on project limitations and capabilities, performance requirements and interfaces.
  • Review modifications to existing software to improve efficiency and performance.
  • Examine new application design and recommend corrections as required

What you'll bring to the role:

  • Senior level (12 to 15 years) data modeling experience
  • Knowledge of BFSI domain and Wealth Management business
  • Critical thinking ability, Strong problem-solving capacity
  • Good written and verbal communication skills.
  • Experience in working with larger agile teams, fleet and squads Secondary skills:
  • Good to have
  • Python & Power BI hands-on experience.
  • Unix Scripting
    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 opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents.

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About Morgan Stanley

Morgan Stanley

Morgan Stanley is an American multinational investment bank and financial services company headquartered at 1585 Broadway in Midtown Manhattan, New York City.

10,001+

Employees

New York

Headquarters

$150B

Valuation

Reviews

10 reviews

4.1

10 reviews

Work-life balance

2.8

Compensation

4.2

Culture

3.7

Career

4.1

Management

2.9

75%

Recommend to a friend

Pros

Great learning opportunities and experience

High salary and bonuses

Good team dynamics and supportive colleagues

Cons

Long hours during peak times

High stress and overwhelming environment

Work-life balance issues

Salary Ranges

6,221 data points

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

49 reports

$109,250

total per year

Base

$95,000

Stock

-

Bonus

-

$73,554

$143,750

Interview experience

6 interviews

Difficulty

3.2

/ 5

Duration

21-35 weeks

Interview process

1

Application Review

2

HR Screen/HireVue

3

Technical/Behavioral Interviews

4

Superday/Final Round

5

Onsite Interview

6

Offer Decision

Common questions

Technical Knowledge

Behavioral/STAR

Investment/Finance Concepts

Case Study

Culture Fit