Executive Director & Head, Data Architecture - Morgan Stanley Investment Management

Morgan Stanley•1585 Broadway- NY, NY

9d•$200,000 - $300,000

About The Position

Morgan Stanley Investment Management (MSIM) is seeking an experienced Data Architect to play a critical role in shaping and driving the transformation of its data capabilities. The role will define the strategic direction and architecture for data across MSIM’s investment platform, establishing principles, patterns, standards, and roadmaps. The Data Architect will collaborate with business, technology, operations, data engineering, analytics, AI, security, and governance teams to translate business strategy into scalable data architecture, ensuring data is treated as an enterprise asset. This position offers a unique opportunity to influence how MSIM thinks about and uses data at an organizational and platform level, requiring a blend of technical depth, strategic thinking, and the ability to drive adoption across multiple teams. The successful candidate will create a structure that makes enterprise data easier to discover, trust, govern, integrate, and consume, moving towards reusable enterprise capabilities and well-defined data products while maintaining controls in a regulated environment. This role requires operating at both strategic and technical levels.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related discipline, or equivalent professional experience.
Operates with a strong sense of ethics and integrity in their interactions with others and decision making.
Takes accountability and ownership in your work with a focus on long-term value creation.
Track record of fostering a culture of honesty, transparency and accountability within teams.
Proven ability to collaborate across teams to deliver optimal solutions for clients.
A passion for innovation, with a continuous improvement mindset to drive excellence.
Respect for individual differences, with an openness to diverse perspectives.
Engagement in community service, volunteering or corporate citizenship initiatives.
Commitment to mentoring and supporting professional growth of others.
Strong understanding of data security, access control, privacy, resiliency, and enterprise risk considerations.

Nice To Haves

Experience within financial services, asset management, banking, or another highly regulated industry.
Experience leading large-scale data migrations, platform transformations and operating model conversions involving investment management platforms.
Deep understanding of investment management data domains including security master, holdings, positions, transactions, portfolios, benchmarks, performance, compliance, accounting, client reporting, risk and product data.
Institutional experience and experience with Blackrock Aladdin and eFront product suite and data structure preferred
Lead architectural oversight of strategic vendor data platforms and external data providers, ensuring alignment with enterprise standards and long-term operating models.
Demonstrated ability to establish architectural standards while enabling teams to deliver pragmatically.
Strong communication and stakeholder-management skills, with the ability to influence across organizational boundaries.
Knowledge of data mesh, data products, domain-oriented architecture, and federated governance concepts.
Experience integrating third-party and vendor data with internally generated enterprise data.
Familiarity with semantic layers, knowledge graphs, vector databases, RAG architecture, and AI-ready data patterns.
Experience modernizing legacy data estates and migrating workloads to cloud or hybrid-cloud platforms.
Experience with contemporary data platforms and technologies such as Snowflake, Databricks, Spark, Kafka, cloud-native data services, or comparable technologies.

Responsibilities

Define and maintain the enterprise data architecture, including conceptual, logical, and physical data models and architectural standards.
Develop target-state architectures and multi-year roadmaps spanning operational, analytical, and AI-oriented data platforms.
Establish architecture patterns for data ingestion, integration, transformation, storage, consumption, and distribution.
Design architectures that support cloud, data lake/lakehouse, warehouse, streaming, API, and event-driven use cases.
Define standards for data domains, data products, canonical models, metadata, lineage, master/reference data, and interoperability.
Establish end-to-end business and technical lineage across critical investment and operational data flows.
Partner with data engineering teams to translate architecture into scalable, resilient, and maintainable implementations.
Work closely with analytics and AI teams to ensure data architecture supports BI, advanced analytics, machine learning, generative AI, and emerging AI use cases.
Embed data governance, quality, privacy, security, entitlements, retention, and regulatory requirements into architectural designs.
Evaluate technology choices and architectural tradeoffs, balancing scalability, performance, resiliency, security, cost, and operational complexity.
Lead architecture reviews and provide technical guidance across major data initiatives.
Identify opportunities to simplify the data estate, reduce duplication, improve reuse, and retire legacy architecture.
Create clear architecture documentation and communicate complex technical concepts to senior technology and business stakeholders.
Serve as a thought leader on modern data architecture and evolving industry practices.