Director, Data Analysis

Fidelity Investments•Durham, NC

14h•Hybrid

About The Position

Position Description: Leads the development and implementation of data modeling strategies to ensure accountability for initiatives and timelines, while maintaining alignment with enterprise standards on technology, tools, and procedures. Analyzes and interprets data to support the team in making informed and impactful decisions, using Financial Data Taxonomy. Enhances and expedites data analysis using the Informatica Data Catalog tool. Draws on in-depth knowledge of the business or function to provide business unit-wide solutions by developing complex, multi-faceted software applications. Research and recommend new technologies in support of the strategic direction of the business unit and participate in the research and recommendation of appropriate models, methods, tools, and technologies to achieve business-unit-wide solutions.

Requirements

Bachelor’s degree in Computer Science, Computer Applications, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and six (6) years of experience as a Director, Data Analysis (or closely related occupation) performing data analysis and data modeling in the financial services environment, using Tableau, Power BI, and PowerDesigner.
Or, alternatively, Master’s degree in Computer Science, Computer Applications, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and four (4) years of experience as a Director, Data Analysis (or closely related occupation) performing data analysis and data modeling in a financial services environment, using Tableau, Power BI, and PowerDesigner.
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.

Responsibilities

Collaborates with business and technology partners to understand requirements, identify data gaps, and recommend strategic solutions across the domain.
Evaluates objectives, use cases, data requirements, and specifications created by other analysts.
Analyzes and resolves significant data issues during projects or in production environments.
Advocates for best practices in data analysis, including handling Personally Identifiable Information (PII), information barriers, and licensed data.
Defines precise conceptual and logical data models for organizational needs across multiple subject areas.
Designs physical structures for operational systems, data warehouses, and data lakes.
Conducts targeted data analysis to identify risks.
Documents and presents database solutions to stakeholders.
Stays updated on technology trends, especially event-driven processing and Data API developments.
Leads sessions to define requirements, business terms, and logical data models.
Maps technical terms into business terms using the data catalog tool.
Guides the use of tools, techniques, and processes for complex data gathering, analysis, and reporting within a large organization.
Identifies opportunities to use enterprise data models in new projects, to minimize work and avoid data duplication.
Mentors and supports analysts, fostering their growth and development.