Back-end Engineer - Data Platforms

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 workflows.

What you’ll bring to the role:

• 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 (e.g., Spark, Hadoop ecosystem, Kafka, Databricks, 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, 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.

Preferred Qualifications

• Experience within Financial Services, Risk, AML, Transaction Monitoring, Regulatory Technology, or Data Platforms.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with containerization technologies (Docker, Kubernetes).
• Experience building data products supporting advanced analytics, machine learning, or AI workloads.
• Knowledge of data governance, metadata management, and data lineage frameworks.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There’s also ample opportunity to move about the business for those who show passion and grit in their work.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices​ into your browser.

Expected base pay rates for the role will be between $155,000 and $215,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.

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.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.