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Morgan Stanley

Manages investments and advises on financing

Full Stack Developer - Data Engineering

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeMontreal, QC, CanadaNo salary listed

About the Job

Requirements

  • At least 4 years of experience designing and implementing complex database and data solutions alongside full-stack application development.
  • Strong expertise in database and data engineering across multiple database platforms and environments, including PostgreSQL, DB2, SQL Server, Sybase, Snowflake, Azure SQL, MongoDB, Teradata, and Oracle.
  • 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 such as OAuth, service principals, and token-based authentication, and secure application development practices.
  • Experience writing complex Python scripts, particularly designing and optimizing multithreaded, multiprocess, concurrent, and asynchronous solutions.
  • Experience designing and developing AI-powered solutions using large language models, retrieval-augmented generation, and agentic workflows.
  • Ability to build and optimize data pipelines and data architectures.
  • Expertise in performance optimization, scalability, troubleshooting, analytical problem-solving, and software design.
  • Knowledge of French and English is required.

Responsibilities

  • Design and develop resilient on-premises and multi-cloud database solutions using Java, Spring Boot, Angular, and Python.
  • Develop high-performance solutions for large-scale data and metadata operations using Python multithreading and multiprocessing libraries, with robust error handling and resource management in parallel execution environments.
  • Deliver secure, high-performance database and ETL capabilities using the Java Collections Framework, data structures, algorithms, and object-oriented design principles, 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 in unstructured data using natural language processing and automated data masking techniques.
  • Build solutions using pushdown optimization, ELT and ETL, Spark-based data processing and streaming, replication, partitioning, clustering, change data capture, and time-travel debugging.
  • Design and build automations and tooling for firmwide data engineering and application development teams to optimize data processing for their database platforms and user needs.
  • Contribute to system modernization, platform standardization, observability, and cost-efficiency initiatives.
  • Develop solutions using database backup and restore methods, DDL generation and manipulation, database access management, and high-performance schema- and object-level data movement.

Desired Qualifications

  • Exposure to distributed computing tools, such as Apache Spark for Python.
  • Experience building and optimizing data pipelines and data architectures using Talend, Kafka, and/or Informatica.

About the Company

Morgan Stanley

Manages investments and advises on financing

Morgan Stanley advises companies and governments on financing and manages investments for institutions, individuals, and families. Its business combines investment banking and securities trading with wealth management and an asset-management division that invests across public and private markets. Bankers arrange stock and bond sales and advise on mergers, while advisors build client portfolios and fund managers invest money under agreed strategies. The firm earns advisory and management fees, trading revenue, commissions, and interest from lending and deposits. Morgan Stanley was founded as a partnership in 1935 and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1935

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