We’re seeking someone to join our team as a Data Engineering Associate

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 Data & Analytics Engineering position at Associate level, which is part of the job family responsible for providing specialist data analysis and expertise that drive decision-making and business insights as well as crafting data pipelines, implementing data models, and optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI-based techniques.

Morgan Stanley

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

What you will do

• The Data Engineer will support the design and development of big data pipelines and distributed data processing systems for enterprise analytics and data products. This role is ideal for early career engineers with strong fundamentals in Python, Apache Spark, distributed systems, and cloud-based data platforms, and an interest in using AI assisted tools to improve productivity and code quality.

• Assist in building and maintaining large scale data pipelines using Apache Spark and distributed processing frameworks. Support batch and streaming data ingestion and transformation workflows.

• Develop and maintain Python-based data processing and validation components.

• Use AI-assisted development tools (e.g., coding copilots, code review and debugging tools) to improve development efficiency and quality.

• Monitor data pipelines and help ensure data quality, reliability, and observability.

• Collaborate with senior engineers, architects, and analysts on scalable data models and ingestion patterns.

• Participate in testing, deployment, and CI/CD activities for data pipelines.

• Document data flows, pipelines, and operational procedures.

What you will bring

• Bachelor’s degree in computer science, Engineering, or a related field (or equivalent practical experience).

• 3 + years of experience or strong academic/project experience in data engineering or big data systems.

• Working knowledge of Python for data processing and automation.

• Working knowledge of Apache Spark (coursework, internships, or projects acceptable).

• Understanding of distributed systems fundamentals (e.g., partitioning, fault tolerance, scalability).

• Familiarity with cloud platforms (e.g., AWS, Azure, or GCP) and cloud-based data services.

• Exposure to AI-powered developer tools for coding, testing, or documentation.

• Strong problem-solving skills and willingness to learn in a fast-paced environment.

• Comfortable working in Linux/UNIX environments.

What you can expect from Morgan Stanley We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 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.

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 90,000 and150,000 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.