Investment Data Modeler
Whether you're an investment professional, an expert in sales or a technology specialist, you'll find a culture at MFS that supports you in doing what you do best. Our employees work together to reach better outcomes, always favoring the strongest idea over the strongest individual. We put people first and show care and compassion for our community and each other. Because what we do matters - to us as valued professionals and to the millions of people and institutions who rely on us to help them build more secure and prosperous futures. Job Description
In conjunction with the Investment Data Office, the Investment Data Modeler contributes to a long-term strategic initiative to unify and harmonize our investment data. This initiative enables enhanced investment decision making, risk management and client reporting for our multi-asset platform by delivering consistent, timely, accurate and user-friendly data to investors, risk teams and clients.
The Investment Data Modeler, working closely with the Investment Data Architect, is responsible for developing conceptual and logical investment data models, rationalizes to physical data models and determines physical design considerations. The Investment Data Molder uses a family of techniques to describe and visualize information that is critical for making decisions and developing solutions related to MFS Investment Data Harmonization, which includes the data model designs and machine algorithms used in ML data processing. Their work informs the design of many technology artifacts, including databases (both relational and nonrelational), data-integration solutions, runtime models (including message models passed between software services), and end-user visible data marts and data presentation layers.
The Investment Data Modeler develops business-focused models to articulate and achieve consensus on business expressions of investment and other business data that serve as the foundation for many artifacts and programs, such as data governance, data quality, data privacy and security, and investment/business data glossaries.
Reporting to the Director of Investment Data Harmonization and working in conjunction with the Enterprise Data Architecture team, this position will ensure that all enterprise standards, guidelines, practices, and metrics are followed within the Investment Data Models and Artifacts. PRINCIPAL RESPONSIBILITIES :
JOB REQUIREMENTS :
- Develop conceptual/subject area data models for investment data and data flow diagrams in an Agile Software Development environment to support the common data model for Investments.
- Facilitate data requirements conversations with the Investment Data Management office and technical stakeholders while resolving conflicts to drive decisions and consensus.
- Create, document, and maintain logical and physical database models that are compliant with enterprise standards.
- Assist in establishing, maintaining, and enforcing data model and metadata design principles, techniques, and standards.
- Ensure consistency of and across data models (e.g., consistent use of naming convention standards)
- Establish and maintain comprehensive data model and associated metadata documentation including detailed descriptions of business entities, attributes, and data relationships as well as the definition of business rules governing the integrity, archiving, and audit requirements of the data.
- Analyze existing systems using manual or automated data profiling, lineage, impact analysis, and other data analysis methods to reverse engineer data requirements.
- Determine suitable data modeling approach for each project based on business requirements for data capture and access.
- Assist developers with complex query development and performance optimization as associated with data models and their usage.
- Periodically review data models to ensure quality, remove redundancy, ensure resiliency of supported data applications, increase data quality and data flow performance.
- Collaborate with the Investment Data Office for the modeling of investment data for the purposes of governing, managing, and increasing the value of investment data.
- Bachelor's Degree with a major in Computer Science, Business, Data Analysis/Processing, Computer Information Systems, or related field is required.
- Minimum three - five (3-5) years data modeling experience in an agile work-environment delivering transactional and operational, reporting/analytical (EDW/Data Lake/NoSQL) solutions.
- Industry: 3 years' experience within the investment and mutual fund management industry, high level knowledge of securities & products, counterparties, positions, and transactions data.
- Understanding of enterprise and report modeling concepts, including relational modeling, dimensional modeling, snowflake schemas, slowly changing dimensions, schema on read, schema on write, irregular dimensions, and surrogate, compound, and intelligent keys.
- Experience with Embarcadero ER/Studio (preferred) and other enterprise-class data modeling and analysis tools.
- Experience with enterprise data warehouse, data lakes, ETL and data integration tools, and multilocational data stores.
- Relational database (Sybase, Oracle or MS SQL Server) experience (SQL scripts, stored procedures, triggers, etc.).
- One to three (1-3) years database administration experience including tuning and optimization.
- Ability to describe the role of data models in supporting diverse use cases such as business processes, BI, data migration or master data management (MDM).
- Experience with ETL (Informatica's PowerCenter), data quality, data profiling and ad-hoc query tools (preferred).
- Experience with data flow diagrams, conceptual/logical/physical data models, data integration, data standards and APIs, data analysis, metadata management, NoSQL modeling and querying, and coding standards, decision modeling, and process modeling.
If any applicant is unable to complete an application or respond to a job opening because of a disability, please contact MFS at 617-954-5000 or email email@example.com for assistance.
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