Principal IT Data Analyst

Fidelity Investments•Durham, NC

9h•Hybrid

About The Position

Position Description: Performs cross-functional collaboration with business partners, product and engineering teams, and architecture to translate complex business requirements into robust data models, and executing sophisticated data analysis. Develops and maintains dashboards and reports, and delivers actionable insights via Tableau and Power BI dashboards while working in an Agile environment. Automates business processes using automation tools Camunda modeler and Power platform (Power Automate and Power apps) to drive business efficiency. Possesses working knowledge of Application Programming Interfaces (APIs).

Requirements

Bachelor’s degree in Business Research, Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and five (5) years of experience as Principal IT Data Analyst (or closely related occupation) performing data analysis using visualization tools – Snowflake, and Tableau or Power BI – in a financial services environment.
Or, alternatively, Master’s degree in Business Research, Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Principal IT Data Analyst (or closely related occupation) performing data analysis using visualization tools – Snowflake, and Tableau or Power BI – in a financial services environment.
Demonstrated Expertise (“DE”) migrating legacy reporting for business processes (brokerage processes --alternative investments, treasury, margin, and Tax) into modernized analytical views, using metadata management tools (Collibra and Alation), SAP Business Objects, and Snowflake.
DE designing and implementing automation using Camunda Modeler (Business Process Model and Notation (BPMN)) for business processes (brokerage processes -- alternative investments, treasury, margin, and tax); and building integrated workflows and applications that enhance operational efficiency, using the Microsoft Power Platform (Power Automate, Power Apps, Power BI, and Dataverse).
DE analyzing user journeys using Pendo.io data to track every user interaction (clicks, page views, and navigation paths), and to import data into Power BI and Tableau to build monitoring dashboards.
DE engineering end-to-end data solutions by developing automated data pipelines (SQL, Python, and Jupyter) for cross-database linking to design critical Key Performance Indicator (KPI) reporting on Tableau and Power BI; and creating robust regulatory reporting controls on secure databases (Oracle, Snowflake, and Amazon Web Services (AWS)) within a financial services environment.

Responsibilities

Collaborates with business partners, and engineering and product teams to convert business requirements into conceptual data models and complex SQL queries.
Analyzes large, complex datasets to uncover trends, patterns, and insights that inform business decisions.
Communicates findings effectively to both technical and non-technical stakeholders.
Documents and understands data lineage from source to consumption, ensuring transparency and traceability.
Collaborates cross-functionally to support data-driven decision-making across the organization.
Conducts complex projects and participates in Agile project delivery, taking ownership of deliverables and driving progress through incremental development.
Develops and implement techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software.
Applies data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets.
Visualizes, interprets, and reports data findings.
Analyzes, manipulates, and processes large sets of data using statistical software.
Cleans and manipulates raw data using statistical software.
Identifies business problems or management objectives that can be addressed through data analysis.
Analyzes data to inform operational decisions or activities.
Determines appropriate methods for data analysis.
Prepares analytical reports.