Principal Data Analyst

Job Description:

Position Description:

Creates scalable documented data design solutions using PL/SQL and Extract, Transform, Load (ETL) tools. Provides data design solutions for cross program initiatives. Develops data quality review strategies. Advocates for adoption of Data Application Programming Interface (API) adoption and reuse. Increases data fluency and literacy across business units. Innovates the product development process to allow the company to continually improve and maintain market leadership in the market. Identifies opportunities to leverage enterprise data model for new projects, improve efficiencies, and eliminate data redundancy. Analyzes user requirements, procedures, and problems to automate or improve existing systems-- reviewing computer system capabilities, workflow, and scheduling limitations.

Primary Responsibilities:

• Enforces data modeling and data design practices.

• Models data defining conceptual data models focusing on business data needs across subject areas.

• Delivers physical database design form logical models.

• Participates in requirement and analysis sessions with business and technical staff to analyze data requirements.

• Develops a platform for asset management data projects.

• Provides end-to-end solution and design for projects.

• Designs a data catalog product for asset management.

• Maintains factsheets for asset management.

• Engagement with the Asset Management Data Office in key areas such as Data Management in common areas, ADAPT, Data Quality, Data Lineage and Catalog, Data Fluency and Learning, Data Access.

• Own the Asset Management Data Taxonomy & Subject Area Governance.

• Provide the data design solutions for cross program initiatives.

• Influence the Data Quality Check Strategy.

• Promote Data API Adoption and reuse.

• Enhance data fluency and literacy across AM.

• Support the complete landscape of Environmental, Social and Governance(ESG) Strategy Program.

• Contribute innovative ideas to the product development process to allow the company to continually improve and maintain market leadership in the Asset Management domain.

Education and Experience:

Bachelor’s degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and five (5) years of experience as a Principal Data Analyst (or closely related occupation) performing data analysis and design in a financial services environment.

Or, alternatively, Master’s degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and three (3) years of experience as a Principal Data Analyst (or closely related occupation) performing data analysis and design in a financial services environment.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) performing data analytics for business users based on requirements using SQL analytical functions and Informatica EDC (Enterprise Data Catalog); creating and implementing data quality checks to ensure the accuracy of data for business use using Informatica EDQ; and providing data support to data engineering teams during production implementation.

• DE creating Entity-Relational (ER) Data Models and Data Warehouse (DW) Data Models- conceptual models (to be presented to information architects), logical models (for business stakeholders), and physical data models (to be implemented in databases); proposing, designing, and implementing ER entity relationship or DW models based on business requirements; creating conceptual, logical, and physical data models using SAP PowerDesigner; and generating DDLs (Data Definition Language) for physical implementation of tables using SAP PowerDesigner.

• DE acting as the liaison between business and technology partners to translate business requirements into technical design solutions; creating business requirement documents in Microsoft Word to document requests from business partners and define the technical components of work to be done by data engineering teams; and collaborating with technology partners to analyze data and create a Source-To-Target (STM) mapping document using TOAD in MS Excel.

• DE planning, designing, and implementing DATA API signatures for RESTful APIs using OpenAPI Specification (OAS); using the SwaggerHub platform for creating, editing, and organizing API definitions; and collaborating with the team members and using Swagger Hub API exploratory features for API socialization.

#PE1M2

Certifications:

Category:Information Technology

Fidelity’s working model blends the best of working offsite with maximizing time together in person to meet associate and business needs. Currently, most hybrid roles require associates to work onsite all business days of one assigned week per four-week period (beginning in September 2024, the requirement will be two full assigned weeks).