Vice President – Lead Data Engineering & AI

Morgan Stanley; Mumbai City; On-site; INR 20,000,000 - 32,000,000; Full time

Job summary

Morgan Stanley seeks a Vice President to lead Data Engineering & AI within Finance Technology. You will architect enterprise-scale data platforms, drive GenAI adoption, and oversee LLM orchestration and governance across finance data assets.

You will mentor engineers, collaborate with global stakeholders, and deliver scalable data and AI solutions that enable intelligent data access and automation in a regulated finance environment.

Qualifications

• 10+ years of experience in data engineering, data architecture, or related roles.
• At least 6 years’ relevant experience to find the skills required for this role.
• Deep expertise in SQL, data modeling, ETL, and scalable data pipelines.
• Strong hands-on experience with cloud data platforms, preferably Snowflake.
• Mandatory: strong domain knowledge in finance or related industries.
• Experience designing AI/GenAI solutions for enterprise data and analytics.
• Experience building natural language interfaces over enterprise data.
• Hands-on experience integrating AI capabilities with enterprise data platforms.
• Experience with evaluation frameworks for LLM-based applications.
• Strong understanding of AI governance, security, and responsible AI controls.

Responsibilities

• Lead architecture, design, and implementation of enterprise-scale data platforms.
• Drive adoption and integration of GenAI, LLMs for ETL automation and data enrichment.
• Design AI-powered data interaction capabilities, including natural language interfaces.
• Architect and implement RAG-based solutions for trusted AI workflows.
• Lead LLm orchestration and agent-based AI patterns with Snowflake Cortex.
• Establish evaluation frameworks for AI solutions, including safety and grounding.
• Ensure security, governance, and auditability in regulated finance environments.
• Provide technical leadership and mentorship to a data engineering team.
• Collaborate with stakeholders to define data and AI strategy and deliverables.
• Champion modern SDLC practices including CI/CD and agile methodologies.

Skills

Data engineering

Data architecture

SQL mastery

Cloud platforms

GenAI adoption

LLM integration

Tools

Snowflake

Snowflake Cortex

Job description

Vice President - Lead Data Engineering & AI

Profile Description

We’re seeking someone to join ourFRPPE Techteam as Lead Data Engineering & AI in Finance Technology to lead the design, development, and implementation ofenterprise-scale data warehouse, reporting, analytics, and AI-enabled data solutions, preferably on cloud platforms such asSnowflake.

This role requires a strong leader with a blend ofdeep data engineering expertiseandapplied AI / GenAI architecture experienceto build intelligent, scalable solutions across finance data platforms. The ideal candidate will help shape the next generation of data products by enablingnatural language interaction with enterprise data,retrieval-augmented generation (RAG),LLM orchestration,agent-based workflows, andevaluation frameworksfor safe and effective AI adoption.

About Finance Technology

Finance Technology at Morgan Stanley delivers innovative solutions for regulatory and financial reporting, general ledger, P&L calculations, and analytics. The team leverages advanced data platforms, modern engineering practices, and is a pioneer in leveragingGenAI for finance productivity-building innovative solutions for automation, insight generation, and efficiency.

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 aLead Data Engineering & AI role within the job family responsible for developing and maintaining software solutions that support business needs, with an expanded mandate to driveAI-powered data access, automation, and decision-support capabilities.

Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and communities in more than 40 countries around the world.

What you’ll do in the role

Responsibilities

• Lead the architecture, design, and implementation ofenterprise-scale data platforms, including data warehousing, semantic modeling, reporting, analytics, and data distribution solutions.

• Drive the adoption and integration ofGenAI, LLMs, and modern AI/ML techniquesfor ETL automation, data enrichment, reporting commentary, and intelligent data distribution across the enterprise.

• Design and buildAI-powered data interaction capabilities, includingnatural language-to-data experiences, conversational access layers, and enterprise search over structured and unstructured finance data.

• Architect and implementRAG-based solutionsthat combine enterprise data sources, metadata, business rules, and contextual retrieval to support trusted AI-assisted workflows.

• Build and governLLM orchestration patterns, including prompt design, tool usage, model routing, context grounding, and secure integration with enterprise data systems.

• Lead the development ofagent-based AI solutions, including integration with platforms such asSnowflake Cortex / Snowflake agentsor equivalent frameworks, to enable intelligent querying, summarization, and workflow execution on top of governed data assets.

• Establish and operationalizeevaluation frameworksfor AI solutions, including response quality, factual grounding, latency, safety, explainability, and business outcome measurement.

• Ensure AI solutions are designed with strong controls forsecurity, governance, entitlements, auditability, and responsible AI practices, particularly in regulated finance environments.

• 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, architects, and cross-functional teams to definedata and AI strategy, requirements, and deliverables aligned with organizational goals.

• Champion modernSDLC practices, including automated testing, CI/CD, and agile methodologies, to ensure high-quality, scalable, and maintainable data and AI solutions.

• Drive automation, data quality, observability, and engineering best practices across all data engineering and AI-enabled solutions.

• Manage stakeholder relationships, communicate project status, and proactively address risks, dependencies, and challenges.

• Champion the adoption of emerging technologies and methodologies to enhance data capabilities, AI enablement, and business value.

What you’ll bring to the role

Required Skills

• 10+ years of experiencein data engineering, data architecture, or related roles, with a proven track record of delivering enterprise-level solutions.

• At least6 years’ relevant experiencewould generally be expected to find the skills required for this role.

• Deep expertise inSQL, data modeling, ETL, and building scalable data pipelines.

• Strong hands-on experience withcloud data platforms, preferablySnowflake, and modern data engineering tools.

• Mandatory: Strong domain and functional knowledge infinance, investment banking, or related industries.

• Demonstrated experience designing and implementingAI / GenAI solutions for enterprise data and analytics use cases, includingRAG architectures, LLM integrations, prompt engineering, model orchestration, and retrieval pipelines.

• Experience buildingnatural language interfaces over enterprise data, enabling business users to interact with governed data systems using AI-assisted experiences.

• Hands-on experience integrating AI capabilities with enterprise data platforms, includingSnowflake Cortex / agentic AI patterns / AI-assisted query or workflow frameworks.

• Experience defining and operationalizingevaluation and testing frameworks for LLM-based applications, including quality benchmarking, hallucination detection, grounding validation, and business acceptance criteria.

• Strong understanding ofAI governance, model risk, security, data privacy, and responsible AI controlsin enterprise environments.

• Demonstrated experience leveragingGenAI, Copilot, or AI-based engineering toolsfor design, development, code completion, code review, documentation, and automated test case generation.

• Proven ability to lead, motivate, and develop high-performing teams.

• Excellent problem-solving, analytical, and communication skills.

• Experience managing stakeholder relationships and delivering complex projects in a global environment.

• Strong understanding of modernSDLC, agile delivery, and innovation in data engineering and AI engineering.

• Experience withautomated testing, testing frameworks, and production-grade release practices.

Additional Skills (Good to Have)

• Familiarity withPower BI, Apache Airflow, and OLAP tools.

• Experience withPython, Shell scripting, workflow automation, and AI application development frameworks.

• Exposure tovector search, embeddings, semantic retrieval, knowledge grounding, and metadata-driven AI architectures.

• Experience withagent frameworks, orchestration tooling, or conversational AI platformsused in enterprise settings.

• Exposure toregulatory and financial reporting requirements.

• Demonstrated track record of drivinginnovation and GenAI adoptionin data engineering projects.

• Passion for continuous learning, business impact, and solution-oriented leadership.

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.