Data Engineering Snowflake Lead Engineer _ Vice President _Data Engineering

Reposted Yesterday
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Fintech • Financial Services
The Role
Lead the design, development, and maintenance of data infrastructure, pipelines, ETL processes, and data platforms using Snowflake, Python, SQL, Databricks, and cloud services. Optimize systems for scalability, implement data quality and governance standards, support structured and unstructured data, collaborate with stakeholders, conduct code reviews, document solutions, and contribute to architecture and knowledge-sharing initiatives.
Summary Generated by Built In

Data Engineering Snowflake Lead Engineer _ Vice President _Data Engineering 

We’re seeking someone to join our ETS (Enterprise Tech & Services) (Architecture & Modernization) team as a Data Engineering Snowflake Lead to manage, develop and design the data infrastructure for our Data AI platforms with good exposure on Data Engineering, Data Modeling, Snowflake, Python and SQL/PLSQL. Experience in Snowflake Cortex will be added advantage.

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 a Lead Data Engineer position at Vice President Level, which is part of the job family responsible for developing and maintains software solutions that support business needs. 

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:

  • Develop and maintain data pipelines and ETL (Extract, Transform, Load) 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 stakeholders across technology and business units to understand their data needs and translate them into technical solutions and provide data-driven insights.

  • Contribute to the documentation and knowledge sharing within the team, creating, and maintaining technical documentation and training materials.

  • Participate in code reviews and contribute to the improvement of development processes.

  • Contribute to the broader data architecture community through knowledge sharing, presentations.

What you’ll bring to the role:

  • 8 years+ of being a practitioner in data engineering or a related field.

  • Proficiency in programming skills in Python.

  • Experience with data processing frameworks like Apache Spark or Hadoop.

  • Strong experience of database systems (SQL and NoSQL).

  • Experience working on Snowflake and Databricks.

  • Experience on Snowflake Cortex is must.

  • Familiarity with cloud platforms (AWS, 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 (e.g., Kafka).

  • Experience with version control systems (e.g., Git).

  • Experience using Jupyter notebooks for data exploration, analysis, and visualization.

  • Excellent communication and collaboration skills.

  • Ability to work independently and as part of a geographically distributed team.

  • At least 6 years' relevant experience would generally be expected to find the skills required for this role. 

  • Nice to have

  • Familiarity with data visualization tools (e.g., Tableau, Power BI).

  • Familiarity with data governance and security best practices (e.g., data access control, data masking).

  • Experience with Agile methodologies.
    Familiarity with data catalog and metadata management tools (e.g., Collibra).
    Familiarity with CI/CD pipelines and DevOps practices.

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 opportunity employer committed to building and maintaining a workforce that is diverse in experience and background.  Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.

Skills Required

  • At least 8 years of experience in data engineering or a related field
  • At least 6 years of relevant experience may generally be expected
  • Proficiency in Python
  • Experience with Apache Spark or Hadoop
  • Strong experience with SQL and NoSQL database systems
  • Experience with Snowflake and Databricks
  • Experience with Snowflake Cortex
  • Familiarity with 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 or streaming platforms such as Kafka
  • Experience with version control systems such as Git
  • Experience using Jupyter notebooks
  • Excellent communication and collaboration skills
  • Ability to work independently and within a geographically distributed team
  • Familiarity with Tableau or Power BI
  • Familiarity with data governance and security practices, including access control and data masking
  • Experience with Agile methodologies
  • Familiarity with data catalog and metadata management tools such as Collibra
  • Familiarity with CI/CD pipelines and DevOps practices

Morgan Stanley Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Morgan Stanley and has not been reviewed or approved by Morgan Stanley.

  • Parental & Family Support Family support is extensive, with paid parental leave for all parents, adoption and fertility assistance, backup childcare, and eldercare resources. Feedback suggests these programs meaningfully enhance the overall package and help with retention.
  • Healthcare Strength Health coverage spans medical, dental, vision, mental‑health access, care navigation, and expert second opinions. Convenient primary care access and condition‑specific support reinforce the depth of healthcare coverage.
  • Equity Value & Accessibility Equity compensation and stock ownership are positioned as core motivators that encourage commitment and retention. Feedback suggests education and support are provided to help participants manage equity and related financial benefits.

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The Company
HQ: New York, NY
87,899 Employees

What We Do

Morgan Stanley mobilizes capital to help governments, corporations, institutions and individuals around the world achieve their financial goals. For over 85 years, the firm’s reputation for using innovative thinking to solve complex problems has been well earned and rarely matched. A consistent industry leader throughout decades of dramatic change in modern finance, Morgan Stanley will continue to break new ground in advising, serving and providing new opportunities for its clients. Morgan Stanley is committed to maintaining the first-class service and high standard of excellence that have always defined the firm. At its foundation are five core values — putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back — that guide its more than 60,000 employees in 1,200 offices across 41 countries.

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