MSIM is at an important point in the evolution of its data capabilities. As a global investment manager with significant scale, continued growth, an increasingly diverse investment platform, and growing demand for data, analytics, and AI, we have a compelling opportunity to reimagine how data is organized, governed, architected, and consumed across the firm.
We are seeking an experienced Data Architect to play a critical role in shaping and driving this transformation. The role will define the strategic direction and architecture for data across the breadth of MSIM’s investment platform—including Public Markets, Private Markets, and Parametric—and establish the principles, patterns, standards, and roadmaps that will serve as a common blueprint for how MSIM architects and manages data.
The Data Architect will work across business, technology, operations, data engineering, analytics, AI, security, and governance teams to translate business strategy and capabilities into durable, scalable data architecture. This role will help ensure that data is treated as an enterprise asset, enabling trusted data, advanced analytics, artificial intelligence, and business applications while simplifying an increasingly complex data landscape.
This is a unique opportunity to influence not simply the design of individual data platforms, but how MSIM thinks about and uses data at an organizational and platform level. The successful candidate will combine strong technical depth and architectural judgment with strategic thinking, the ability to establish and enforce enterprise-wide principles, and the influence to drive adoption and implementation across multiple businesses, platforms, and teams.
The successful Data Architect will create a structure that makes enterprise data easier to discover, trust, govern, integrate, and consume. They will help move the organization from project-specific data solutions toward reusable enterprise capabilities and well-defined data products, while maintaining the controls, resiliency, and security expected in a regulated environment. This role requires someone who can operate at both the strategic and technical levels—defining the target state while remaining close enough to implementation to ensure that architectural principles translate into practical outcomes.
Key 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.
Preferred Qualifications
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.
Strong understanding of data security, access control, privacy, resiliency, and enterprise risk considerations.
Bachelor's degree in Computer Science, Engineering, Information Systems, or a related discipline, or equivalent professional experience.
Who you are
Operates with a strong sense of ethics and integrity in your 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.
Expected base pay rates for the role will be between $200,000 and $300,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
