Back-end Engineer - Data Platforms

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Back-end Engineer - Data Platforms position at the Vice President level, which is part of the job family responsible for developing and maintaining software solutions that support business needs.

Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals.

Interested in joining a team that’s eager to create, innovate and make an impact on the world? Read on.

We are seeking a highly skilled Vice President Backend Software Developer to design, build, and scale enterprise-grade data platforms and backend services supporting critical business and regulatory workloads. The ideal candidate combines deep technical expertise in distributed data processing, modern data architecture, and system design with strong engineering leadership, code quality, and AI-enabled development practices.

As a VP Backend Software Developer, you will be responsible for architecting and delivering scalable backend systems, data pipelines, and platform capabilities that process large volumes of structured and unstructured data. You will partner with product owners, architects, data engineers, and business stakeholders to build resilient, high-performance solutions while establishing engineering best practices across the development lifecycle.

This role requires strong expertise in Python, PySpark, Big Data technologies, Snowflake, Graph Technologies, System Architecture, and AI-assisted software development.

What you’ll do in the role:

Software Engineering & Development 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.

Data Engineering & Platform Development 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.

Architecture & Design 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.

Graph & Advanced Data Technologies Design and implement graph-based data models and analytics solutions.

Build relationships and network-based insights using graph technologies.

Evaluate graph databases and related technologies to solve complex business problems.

Engineering Excellence 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.

AI-Enabled Development 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…