Position: Data/Snowflake Architect
Location: NYC, NY (3 days onsite is must)
Duration: 12 Months
We are seeking an experienced Data / Snowflake Architect to join our Assurance & Legal Technology department overseeing Snowflake/Postgres distributed database platform deployments. This role involves comprehensive data analysis, data schematic design, performance tuning, and leveraging modern technologies to source, sanitize, and curate data into a gold data source for advanced analytics and reporting. You will play a key role in driving modernization, automation, and performance optimization across our Cloud/On-Prem data-platform ecosystem.
Responsibilities
Design, implement, and manage large-scale distributed database systems using Snowflake and Postgres.
Lead the architecture and deployment of database clusters across hybrid cloud environments (AWS, Azure).
Develop and maintain automation frameworks for provisioning, monitoring, and scaling database infrastructure.
Collaborate with data engineering, platform, and application teams to ensure high availability, security, and performance.
Drive adoption of best practices for schema design, query optimization, and data lifecycle management.
Implement robust backup, disaster recovery, and compliance strategies.
Mentor junior engineers and contribute to cross-training initiatives across database technologies.
Govern how both structured and unstructured data is ingested, processed, and engineered for context.
Ensure high availability, disaster recovery, and performance tuning across multi-region deployments.
Collaborate with senior product, engineering, and audit leadership to influence business strategy and ensure solutions are built on a sound architectural foundation.
Architect and oversee the design and development of data and context engineering capabilities using Snowflake and PostgreSQL.
Make critical design decisions that enable seamless integration into Data Analytics, Business Intelligence Reporting, and AI agent workflow capabilities.
Establish and enforce data governance, quality standards, and validation frameworks.
Guarantee the integrity, security, and reliability of all data solutions.
Drive modernization initiatives includingcloud-native database adoption,serverless architecture, andAI/ML integration.
Evaluate and implement emerging technologies to improve platform efficiency and developer experience.
Drive the future of audit technology by leading architectural innovation.
Champion the evaluation and adoption of next-generation data platforms, knowledge graphs, and advanced data fabrics.
Act with integrity, professionalism, and personal responsibility to uphold Morgan Stanley s respectful and courteous work environment.
Qualifications
Minimum 10 years of recent experience in data architecture, data engineering, or a similar field.
Hands-on expertise with PostgreSQL and Snowflake administration and performance tuning.
Strong scripting and automation skills (Python, Ansible, etc.).
Familiar with Cloud Based Architectures /Data-Warehousing Platforms, prior experience / knowledge in Snowflake Design Patterns and migration workflow would be a plus.
Prior exposure building ML and generative AI solutions using Snowflake Cortex Analyst, Search, AI SQL, Snowflake ML, and Snowpark Container Services.
Proven record of architecting and delivering large-scale data warehouse modeling and reporting solutions for enterprise systems.
A bachelor s degree from an accredited college or university is required. A master's degree in computer science, engineering, or a related technical discipline is preferred.
Expertise in architecting cloud-native data ecosystems using platforms such as Snowflake, Databricks, Talend, SPARK, Power BI, and Microsoft Fabric.
Deep knowledge of designing solutions that incorporate Retrieval-Augmented Generation (RAG) and vector search (e.g., Azure AI Search).
In-depth understanding of architectural patterns for processing and modeling both structured transactional data and unstructured information.
Experience with transactional processing and AI/ML applications.
Demonstrated experience defining architectural principles, data governance policies, and technology standards within a large-scale, regulated, and Agile Software Development Life Cycle (SDLC) environment.
Exceptional problem-solving, communication, collaboration and leadership skills.
Ability to articulate strategic technical vision, influence executive-level stakeholders, and guide solutions for complex business problems.
