Principal Data Modeler

Job Description:

Position Description:

Develops conceptual, logical, and physical data models that align with business domains and enterprise architecture. Maintains consistent application of data standards, naming conventions, and modeling best practices across all projects. Builds structured and organized representations of data, which serve as a blueprint for efficient data storage and retrieval, using data modeling tools -- SAP Power Designer and ERWIN. Creates and delivers data mapping specifications and data models for large reporting platforms, using Oracle, Hadoop, Postgres, and Microsoft SQL Server. Creates new data models and software structures to detail the flow of data from origination to consumption, using data platforms -- Oracle, Snowflake, Hadoop, Postgres, and Microsoft SQL Server, by applying data design patterns -- Online Transaction Processing (OLTP) recordkeeping, Operational Data Stores (ODS), Master Data Management (MDM), warehousing, and data lakes. Creates and delivers data lake solutions and data warehouses using database technologies Snowflake on Amazon Web Services (AWS). Performs database querying by leveraging SQL.

Primary Responsibilities:

• Collaborates with solution architects, data engineers, and business stakeholders to design models that support scalability, interoperability, and compliance.
• Defines and leads enterprise-level data strategy and analytics initiatives.
• Maintains technical requirements in a multi-platform and highly integrated data environment using dimensional, relational, and unstructured modeling strategies.
• Designs data validation procedures, Extract, Transform, Load (ETL) development, and data modeling and mapping documentation.
• Discovers, designs, and delivers database design solutions for key business partners.
• Develops and implements advanced data solutions to support analytics and reporting capabilities.
• Confers with systems analysts and other software engineers and developers to design systems and to obtain information on project limitations and capabilities, performance requirements, and interfaces.
• Performs analysis in the form of research, gap analysis, data mining, and data profiling.
• Collaborates and influences across all levels of the organization, including written, verbal, and technology illustrations.
• Advises senior leadership on data infrastructure and technology solutions.
• Provides guidance to junior data modelers.
• Performs independent and complex technical and functional analysis for multiple divisional initiatives.
• Develops innovative solutions to support scalable, secure, and high-performance data environments.

Education and Experience:

Bachelor’s degree in Computer Science, Engineering, Information Technology, Cybersecurity, Information Systems, Data Analytics, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Principal Data Modeler (or closely related occupation) performing relational data modeling and analysis on relational databases using SQL in a financial services environment.

Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Cybersecurity, Information Systems, Data Analytics, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Principal Data Modeler (or closely related occupation) performing relational data modeling and analysis on relational databases using SQL in a financial services environment.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) designing complex relational databases using data modeling techniques to create conceptual, logical, and physical models according to standards, taxonomy, and best practices.
• DE generating Data Definition Language (DDL) scripts (forward-engineer) and Data Manipulation Language (DML) scripts to create and update physical databases; and performing reverse-engineering of system databases to create additional external tables and columns to gather data requirements from the source databases.
• DE building source-to-target mapping documents, profiling, mining, specifying, extracting, cleansing, and analyzing large data warehouses, using SQL Developer, Toad, and Python; generating insights for business and end users using SQL reports; writing SQL queries and views against the database (SQL Server and Oracle) and generating reports; and modifying existing SQL queries to improve query performance.
• DE conducting root cause analysis using SQL queries for business requests; collaborating with business groups to understand application requirements; coordinating with enterprise cross-functional and non-technical teams, preparing functional specifications, and translating them into technical solutions; building ad hoc tables and reports for required use cases; and analyzing and interpreting data flowing from multiple work streams.

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Fidelity’s Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Certifications:

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Please be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.