The Vice President Backend Software Developer role at Morgan Stanley focuses on designing, building, and scaling enterprise-grade data platforms and backend services. This position requires a combination of technical expertise in distributed data processing and strong engineering leadership. The ideal candidate will work closely with product owners, architects, and business stakeholders to deliver high-performance solutions. The role emphasizes the importance of engineering best practices and AI-enabled development.

• Bachelor's or master's degree in computer science, Engineering, Information Technology, or related field.
• 8+ years of software engineering experience with a strong focus on backend development.
• Expert-level programming experience using Python.
• Strong hands-on experience with PySpark and distributed data processing.
• Experience with Big Data technologies such as Spark, Hadoop ecosystem, Kafka, Databricks, and Delta Lake.
• Strong expertise in Snowflake architecture, data modeling, and performance optimization.
• Experience designing and implementing large-scale data pipelines and data platforms.
• Experience with Graph Technologies and graph-based data solutions.
• Strong understanding of System Architecture, Application Design Patterns, Microservices Architecture, Event-Driven Architectures, Distributed Systems, and API Design.
• Proven experience conducting architecture and code reviews.
• Strong understanding of CI/CD, DevOps, testing frameworks, and software delivery best practices.
• Experience using modern AI developer tools and AI-assisted engineering practices.

• Design, develop, and maintain scalable backend applications and services.
• Build high-performance distributed data processing solutions and big data frameworks.
• Develop reusable frameworks, APIs, and platform services supporting enterprise applications.
• Drive design and implementation of real-time and batch processing architectures.
• Design and implement robust data pipelines for ingestion, transformation, validation, and consumption.
• Develop scalable solutions by leveraging Snowflake and modern cloud-based data platforms.
• Optimize large-scale data processing workloads for performance, reliability, and cost efficiency.
• Support data governance, lineage, observability, and data quality initiatives.
• Lead system architecture discussions and define long-term technical roadmaps.
• Produce high-quality architecture and design documentation.
• Evaluate technologies, patterns, and frameworks to improve platform capabilities.
• Ensure solutions meet security, resiliency, scalability, and regulatory requirements.
• Design and implement graph-based data models and analytics solutions.
• Build relationships and network-based insights using graph technologies.
• Conduct design reviews and code reviews to ensure adherence to engineering standards.
• Establish best practices for testing, CI/CD, performance tuning, and operational excellence.
• Promote software craftsmanship, maintainability, and automation across teams.
• Mentor junior engineers and provide technical leadership.
• Leverage AI-assisted development tools to improve engineering productivity and code quality.
• Drive adoption of AI-powered coding, documentation, testing, and review capabilities.
• Identify opportunities to integrate AI and automation into engineering workflows.

• Morgan Stanley offers extensive benefits that support employees’ careers, health, finances, and families, including top-tier medical coverage, mental health support, generous parental leave, fertility and family-building benefits, and robust retirement and stock purchase plans. Employees also gain access to continuous learning and networking opportunities, volunteer and giving programs aligned with the firm’s values, and hundreds of lifestyle perks like discounted products, cultural and entertainment tickets, and commuter savings.