IT Data Infrastructure Architect VP

IT Data Infrastructure Architect - Vice President

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking securities investment management and wealth management services. Our success depends on the talent and passion of our people. We offer a superior foundation for building a professional career where you can learn achieve and grow.

Technology is the key differentiator that enables us to manage global businesses and serve clients on a resilient secure and innovative platform. Our award-winning technology platforms drive business excellence and innovation across complex financial markets.
Technology Architecture & Modernization

The Architecture & Modernization (AM) team drives the Firms multi-year technology modernization roadmap focusing on architecture frameworks product delivery and developer enablement. We aim to modernize technologies and practices to deliver scalable secure and future-ready platforms.

Role Overview
We are seeking a Data Infrastructure Architect with 7 years of experience in designing and governing enterprise-scale data platforms within regulated environments. The role ensures data is accessible trusted secure and optimized for analytics machine learning and AI-driven solutions. Ideal candidates will either already have transitioned to or be ready to transition from a hands-on delivery role to strategic influence shaping data architecture standards and guiding technology decisions across the organization.

Key Responsibilities

• Architecture & Design

• Develop and execute data infrastructure architecture strategies roadmaps and blueprints for enterprise IT initiatives.

• Divisional Data Officer driving data architecture & governance working in close collaboration with Firmwide Data Office and other Divisional Data Officers

• Collaborate with SME teams building and scaling data platforms (data lakes warehouses) across on-prem cloud and hybrid environments.

• Implement semantic layers for consistent governed data views enabling self-service analytics and explainable AI

• Oversee data quality processes and enforce standards to minimize data duplication and ensure trusted data.

• Recommend and implement cloud-native solutions for scalability resilience and business continuity.

• Drive modernization of infrastructure systems through cloud adoption automation and software-defined technologies.

Governance & Compliance

• Conduct architecture reviews ensuring alignment with regulatory security and enterprise standards.

• Maintain reference architectures policies and best practices for data infrastructure.

• Ensure robust data protection encryption and zero-trust security principles.

Collaboration & Stakeholder Engagement

• Promote architectural best practices resolve design challenges and influence technical decisions.

• Partner with enterprise architects engineering teams and SREs to align solutions with IT strategy.

• Provide technical leadership and guidance to engineering and operations teams. Required Technical Skills

• Data Platforms:
  Experience in building & scaling data lakes data warehouses and associated data systems.

• Databases: SQL PostgreSQL;
  MongoDB and cloud-based platforms (e.g. Snowflake Databricks Redshift).

• Semantic Layer:
  Design and implementation for governed reusable data views.

• Data Governance Tools:
  Collibra Alation Talend or equivalent.

• Expertise in ETL tools and processes (e.g. Apache NiFi Talend Informatica)

• Security:
  Data Privacy Data Protection & Encryption frameworks & governance

• Enterprise Architecture Frameworks: TOGAF Zachman; familiarity with ITIL processes.

Additional Helpful

Skills:

• Cloud Platform Awareness:
  One or more of AWS Azure and /or GCP

• Automation & IaC:
  Terraform Ansible Puppet; CI/CD pipelines (Jenkins Git Hub Actions).

• Observability & Monitoring:
  Experience integrating observability and monitoring solutions (Splunk Prometheus Loki Grafana).

AI & Advanced Analytics Exposure:

• LLM Integration:
  Retrieval-augmented generation fine-tuning prompt engineering.

• Generative AI:
  Building and deploying generative AI solutions for data-driven insights and automation.

• Agentic AI:
  Designing agent-based architecture for autonomous workflows and decision-making.

Qualifications & Experience

• 7 years in IT data infrastructure within large regulated enterprises.

• Proven experience in data architecture and modernization initiatives.

• Strong understanding of data security and compliance requirements in financial services.

• Excellent communication problem-solving and stakeholder management skills.

Key Competencies

• Ability to influence technical decisions in complex environments.

• Demonstrated leadership in cross-functional teams

• Strong analytical and strategic thinking.

• Passion for emerging technologies and continuous improvement.

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WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

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