Jobs

Data Engineer (Snowflake)_Associate_Software Engineering
Mumbai, Maharashtra, India
·
On-site
·
Full-time
·
2w ago
Benefits & Perks
•Healthcare
•401(k)
•Flexible Hours
•Remote Work
•Healthcare
•401k
•Flexible Hours
•Remote Work
Required Skills
Python
SQL
Snowflake
dbt
Apache Airflow
Git
Profile Description
Division
We are looking for a Data Engineer (3–5 years) with strong Python programming skills and hands-on experience building modern data platforms using Snowflake, dbt, and Apache Airflow. You will design and develop reliable data pipelines, model and transform data for analytics, and collaborate using Git-based workflows to deliver high-quality, production-ready data solutions. Experience with Power BI and exposure to AI/ML use cases is a plus.
Investment_Management
In the Investment Management division, we deliver active investment strategies across public and private markets and custom solutions to institutional and individual investors.
IMIT App Dev
Operations Technology is responsible for building and operating the technology platform catering to critical business processes at Morgan Stanley including Settlements, Confirmations, Regulatory Reporting, Position Keeping, Corporate Actions processing and other post-trade functions. The Firm operates at scale with up to 60 million trades processed on peak volume days and several trillion dollars of daily settlements with activity ongoing in multiple countries and currencies across the globe. There is a great breadth of financial products that our Operations plant handles across equity and fixed income, from cash products to complex derivatives and loans.
Software Engineering
The Lead will get involved in the design, development, and testing of multi-tier systems and components across the platforms
Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals.
At Morgan Stanley India, we support the Firm’s global businesses, with critical presence across Institutional Securities, Wealth Management, and Investment management, as well as in the Firm’s infrastructure functions of Technology, Operations, Finance, Risk Management, Legal and Corporate & Enterprise Services. Morgan Stanley has been rooted in India since 1993, with campuses in both Mumbai and Bengaluru. We empower our multi-faceted and talented teams to advance their careers and make a global impact on the business. For those who show passion and grit in their work, there’s ample opportunity to move across the businesses for those who show passion and grit in their work.
Interested in joining a team that’s eager to create, innovate and make an impact on the world? Read on…
What you’ll do in the role:
· Design, build, and maintain scalable ETL/ELT pipelines using Apache Airflow (DAG design, scheduling, monitoring, retries, alerting).
· Develop and optimize cloud data warehousing solutions on Snowflake (schemas, performance tuning, clustering/partitioning strategies where applicable, cost awareness).
· Implement analytics engineering best practices using dbt:
o Data modeling (star/snowflake schemas, dimensional modeling)
o Reusable macros, tests, documentation, and lineage
o Environment management (dev/test/prod)
· Write clean, efficient, and maintainable Python code for data ingestion, transformation, orchestration, and automation tasks.
· Ensure data quality and reliability through validation, automated testing, and observability/monitoring.
· Use Git-based workflows (branching, PRs, code reviews) and contribute to CI/CD practices for data pipelines and dbt projects.
· Troubleshoot pipeline failures, resolve data issues, and continuously improve performance and stability.
What you’ll bring to the role:
· 3–5 years of professional experience in Data Engineering or related roles.
· Hands-on experience with Snowflake, dbt, and Apache Airflow in production or enterprise environments.
· Strong programming skills in Python (data processing, APIs, automation, packaging, best practices).
· Solid understanding of data engineering concepts:
o ETL/ELT patterns, orchestration, batch processing (and streaming familiarity is a plus)
o Data modeling, warehousing concepts, and SQL optimization
· Strong SQL skills and experience working with large datasets.
· Working knowledge of Git-based development workflows (feature branches, pull requests, reviews, merging strategies).
Good to Have (Preferred Skills)
· Experience building dashboards or semantic models with Power BI.
· Exposure to AI/ML concepts or enabling AI use cases (feature datasets, data prep for model training/inference, LLM/AI pipeline awareness).
· Kafka (integration / streaming support)
· Great Expectations (data quality checks / validation framework)
Soft Skills
· Strong problem-solving and debugging abilities.
· Good communication skills and ability to work cross-functionally.
· Ownership mindset with attention to data quality, reliability, and documentation.
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
PublicA financial services company that offers securities, asset management, and credit services.
10,001+
Employees
New York
Headquarters
Reviews
3.5
4 reviews
Work Life Balance
3.0
Compensation
2.5
Culture
3.2
Career
3.0
Management
3.0
35%
Recommend to a Friend
Pros
Skills evaluation through business plans and projects
Direct access to senior leadership interviews
Conversational interview format
Cons
Automated resume screening system issues
Focus on formatting over qualifications
Compensation concerns and salary expectations
Salary Ranges
11,766 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
1,682 reports
$114,371
total / year
Base
$96,366
Stock
-
Bonus
$18,005
$77,808
$170,800
Interview Experience
6 interviews
Difficulty
3.0
/ 5
Duration
21-35 weeks
Experience
Positive 16%
Neutral 84%
Negative 0%
Interview Process
1
Initial screening (HR/HireVue)
2
Technical rounds
3
Manager/Senior leadership interviews
4
Final round/Superday
Common Questions
Technical knowledge assessment
Behavioral questions
Role-specific scenarios
Leadership and teamwork examples
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