Full Stack Developer – Data Engineering; Hybrid

We’re seeking someone to join our Data Obfuscation team as a Full Stack Developer – Data Engineering to design and deliver scalable, secure, and reusable data platforms and services that support enterprise data protection and obfuscation initiatives.

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 Cybersecurity Engineering III position at Associate level, which is part of the job family responsible for providing specialist cyber expertise and creating solutions that protect the organization’s systems and networks against actual and potential security threats and vulnerabilities.

Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.

• Design and develop resilient on-prem and multi-cloud database solutions with Java, Spring Boot, Angular, and Python.
• Develop high-performance solutions that efficiently handle large-scale data and metadata operations leveraging Python’s multithreading and multiprocessing libraries and ensure robust error handling and resource management in parallel execution environments.
• Deliver secure, high-performance and efficient database and ETL capabilities using Java Collections Framework, data structures, algorithms, and object-oriented design principles, while ensuring scalability, governance, and reliability.
• Design and develop full-stack applications, including responsive web user interfaces, RESTful APIs, backend services, and integrations with database and ETL platforms.
• Build self-service capabilities, operational dashboards, workflow automation, and metadata-driven solutions using modern web technologies and microservices architectures.
• Develop AI-driven solutions to discover, classify, and protect sensitive information within unstructured data, leveraging advanced natural language processing and automated data masking techniques
• Build solutions with pushdown optimization, ELT, ETL, Spark-based data processing and streaming, replication, partitioning, clustering, change data capture, and time travel debugging.
• Design and build automations and tooling to enable firmwide data engineering and application development teams, helping them optimize data processing based on their specific database platforms and user needs.
• Contribute to strategic initiatives around system modernization, platform standardization, observability, and cost efficiency.
• Develop solutions leveraging database backup and restore methods, DDL generation and manipulation, database access management, schema and object-level high-performance data movement.

• 4+ years of proven track record in designing and implementing complex database and data solutions with full stack application development.
• Strong expertise in database/data engineering across multiple database platforms and environments (e.g., PostgreSQL, DB2, SQL Server, Sybase, Snowflake, Azure SQL, MongoDB, Teradata, Oracle, etc.).
• Hands‑on experience developing full‑stack applications using Java/Spring Boot, Python, REST APIs, and Angular.
• Strong understanding of API design, microservices architecture, authentication mechanisms (OAuth, service principals, token‑based authentication), and secure application development practices.
• Experience in writing complex Python scripts, with a particular focus on building and optimizing multi‑threaded, multi‑process, concurrent, and asynchronous solutions; exposure to distributed computing tools (such as Apache Spark for Python) is an asset.
• Exper…