Distributed-Database Platform Engineer

We are seeking a highly skilled and motivated Distributed-Database Platform Engineer to lead the management and scaling of Snowflake, Postgres, and Greenplum database platforms globally for over 10,000 end-users. The role focuses on modernizing, automating, and optimizing performance across a hybrid cloud infrastructure spanning AWS and Azure.

• Design, implement, and manage large‑scale distributed database systems using Snowflake and Postgres
• Lead architecture and deployment of database clusters across hybrid cloud environments
• 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
• Architect, deploy, and manage large‑scale distributed database systems (Platform Engineering & Operations)
• Ensure high availability, disaster recovery, and performance tuning across multi‑region deployments
• Lead design and implementation of multi‑cloud database strategies
• Build and maintain infrastructure‑as‑code and automation pipelines for provisioning, scaling, and monitoring database clusters (Automation & Scalability)
• Develop self‑healing and auto‑scaling mechanisms to support dynamic workloads
• Drive modernization initiatives including cloud‑native database adoption, serverless architecture, and AI/ML integration (Innovation & Modernization)
• Evaluate and implement emerging technologies to improve platform efficiency and developer experience
• Prior exposure to building ML and generative AI solutions using Snowflake Cortex Analyst, Search, AI‑SQL, Snowflake ML, and Snowpark Container Services (Design & Architecture of AI/ML Solutions)
• Conduct workshops and discovery sessions with client stakeholders, and expose internal teams to AI/ML model training and deployment

• Prior expertise and experience in PostgreSQL and Snowflake administration and performance tuning
• Proven experience managing large‑scale distributed systems; experience with 100K+ clusters preferred
• Strong scripting and automation skills (Python, Terraform, Ansible, etc.)
• Experience with CI/CD pipelines and infrastructure‑as‑code practices
• Familiarity with cloud‑native architectures and services in AWS and Azure
• Excellent problem‑solving, communication, and collaboration skills
• Knowledge of Snowflake Design Patterns and migration workflows advantageous
• Operational experience understanding large‑scale IaaS platforms (Azure/AWS) advantageous
• Experience deploying georedundant databases using third‑party cluster managers such as Patroni or Golden Gate
• Capability to manage Snowflake environment, including virtual warehouse sizing, query performance tuning, cost management, and cortex AI services
• Staying current with Snowflake SaaS offerings, third‑party integrations, and cloud data warehousing trends
• Implement and manage data security, access controls, and encryption policies to ensure data integrity and compliance
• Knowledge of data governance, security, and compliance frameworks

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.

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