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 (A+M) team drives the Firm's 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 AIOversee 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 GCPAutomation & 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…