Data Engineer - Parametric

About Morgan Stanley

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, wealth management and investment management services. With offices in more than 41 countries, the Firm's employees serve clients worldwide including corporations, governments, institutions and individuals. For further information about Morgan Stanley, please visit

Parametric is part of Morgan Stanley Investment Management, the asset management division of Morgan Stanley. We partner with advisors, institutions, and consultants to build portfolios focused on what's important to them and their clients. A leader in custom solutions for more than 30 years, we help investors access efficient market exposures, solve implementation challenges, and design multi-asset portfolios that respond to their evolving needs.

We also offer systematic alpha and alternative strategies to complement clients' core holdings.

This role is part of Parametric's hybrid working model, which includes working in the office 3 days a week and choosing to work remotely or in the office the remaining days of the week.

The Data Management Office ensures that data pipelines are scalable, repeatable, secure, and can serve multiple users. We help facilitate getting data from a variety of different sources, getting it in the right formats, assuring that it adhere to data quality standards, and assuring that downstream users can get that data quickly.

The Data Engineer is responsible for the design, structure, and maintenance of data. A data engineer ensures the accuracy and accessibility of data relevant to an organization or a project. In this role the Data Engineer needs to be able to take business requirements and design and architecture end to end that fully supports the business needs. The Data engineer needs to be proficient in writing and optimizing SQL queries.

They need to be able to document ideas and proposals which will include creating ER diagrams and architectural documents that document the transformation of data throughout its lifecycle.

A successful Data Engineer must possess solid analytical skills and be detail-oriented. This role requires the ability to communicate effectively as part of a larger team within the information technology department. Additionally, you will need to explain complex technical concepts to non-technical staff. Since development of data models and logical workflows is common, a Data Engineer must also exhibit strong visualization skills, as well as creative problem-solving.

• Works with team members to design and implement data solutions in alignment with the project schedule.
• Codes, tests, and documents new or modified data systems to create robust and scalable data platform for our applications.
• Works with developers to make sure that all data solutions are consistent.
• Expands and grows data platform capabilities to solve new data problems and challenges.
• Creates data flow diagrams for all of business systems.
• Implements security and recovery tools and techniques as required.
• Help to create and maintain a data catalog for each project.
• Interprets data results to business customers.
• Design of the logical model and implements the physical database to support business needs.
• Conducts logical and physical database design.
• Designs key and indexing schemes and designs partitioning.
• Develops, tests, implements, and maintains database management applications.
• Constructs and implements operational data stores and data marts.
• Ensures database changes are reviewed and approved according to database design standards and principles.
• Resolves conflicts between models, ensuring that data models are consistent with the ecosystem model (e.g., entity names, relationships and definitions).
• Models best practices in data management.
• Contributes in creating, refining, managing and enforcing data management policies, procedures, conventions and standards.
• Evaluates and provides feedback on future technologies and new releases/upgrades.
• Contributes to the establishment of business continuity & disaster recovery requirements, methods and procedures for data systems and databases.

• Bachelor's in Computer Science, Mathematics, or Engineering or equivalent work experience
• 2+ years of data engineering experience
• 1+ years of experience with Snowflake
• 1+ years of experience in AWS (or similar cloud technologies) cloud stack including S3, IAM, Athena, SNS, SQS, and EMR.
• 2+ years of SQL Server and experience with tools such as SSIS and SSRS
• Programming experience in Python and Linux bash
• Demonstrated experience with agile or other rapid application development methods
• Demonstrated experience with object-oriented design, coding and testing patterns as well as experience in engineering (commercial or open source) software platforms and data infrastructures
• Solid understanding of data modeling and understanding of different data structures and their…