Senior Data Engineer - Vice President

Morgan Stanley • New York, NY

2d • $150,000 - $210,000

About The Position

Lead the design, development, and implementation of enterprise-scale data warehouse, reporting, and analytics solutions, preferably on cloud platforms such as Snowflake. Drive the adoption and integration of GenAI, LLMs, and modern AI/ML techniques for ETL automation, data enrichment, reporting commentary, and intelligent data distribution across the enterprise. Provide technical leadership and mentorship to a high-performing team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement. Collaborate with business stakeholders, technology partners, and cross-functional teams to define data strategy, requirements, and deliverables aligned with organizational goals. Champion modern SDLC practices, including automated testing, CI/CD, and agile methodologies, to ensure high-quality, scalable, and maintainable solutions. Drive automation, data quality, and best practices across all data engineering processes and solutions. Ensure robust data governance, security, and compliance throughout the data lifecycle. Manage stakeholder relationships, communicate project status, and proactively address risks and challenges. Champion the adoption of new technologies and methodologies to enhance data capabilities and business value. 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. 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. Expected base pay rates for the role will be between $150,000 and $210,000 per year at the commencement of employment. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees. It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.

Requirements

• 10+ years of experience in data engineering, data architecture, or related roles, with a proven track record of delivering enterprise-level solutions.
• Deep expertise in SQL, data modelling, ETL, and building scalable data pipelines.
• Strong hands-on experience with cloud data platforms (preferably Snowflake) and modern data engineering tools.
• Strong hands-on experience with Python, Shell scripting, and workflow automation.
• Demonstrated experience leveraging GenAI, LLMs, or AI/ML solutions for enterprise data, reporting, and analytics use cases.
• Proven ability to lead, motivate, and develop high-performing teams.
• Strong domain and functional knowledge in finance, investment banking, or related industries.
• Excellent problem-solving, analytical, and communication skills.
• Experience managing stakeholder relationships and delivering complex projects in a global environment.
• Strong understanding of modern SDLC, agile delivery, and innovation in data engineering.
• Passion for continuous learning, business impact, and solution-oriented leadership.

Nice To Haves

• Familiarity with Power BI, Apache Airflow, and OLAP tools.
• Exposure to regulatory and financial reporting requirements.
• Demonstrated track record of driving innovation and GenAI adoption in data engineering projects.

Responsibilities

• Lead the design, development, and implementation of enterprise-scale data warehouse, reporting, and analytics solutions, preferably on cloud platforms such as Snowflake.
• Drive the adoption and integration of GenAI, LLMs, and modern AI/ML techniques for ETL automation, data enrichment, reporting commentary, and intelligent data distribution across the enterprise.
• Provide technical leadership and mentorship to a high-performing team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement.
• Collaborate with business stakeholders, technology partners, and cross-functional teams to define data strategy, requirements, and deliverables aligned with organizational goals.
• Champion modern SDLC practices, including automated testing, CI/CD, and agile methodologies, to ensure high-quality, scalable, and maintainable solutions.
• Drive automation, data quality, and best practices across all data engineering processes and solutions.
• Ensure robust data governance, security, and compliance throughout the data lifecycle.
• Manage stakeholder relationships, communicate project status, and proactively address risks and challenges.
• Champion the adoption of new technologies and methodologies to enhance data capabilities and business value.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed