Senior IT Data Analyst

Implements data modelling and automation using Artificial Intelligence (AI) and Machine Learning (ML) models for descriptive and predictive analysis in the data lakes at the enterprise level. Represents a direct continuation of the Data and Reporting platform, cloud capability development and modernization initiatives. Applies knowledge of data domains and source systems for numerous business functions. Applies hands‑on experience building and enabling platforms, databases and data migration tools. Provides data solutions using SQL, Python, Jira/Jira Align, Domo and Technology Management Data Lake. Enforces data quality controls using automated processes to establish analytic standards, best practices, and influence strategic decisions. Builds viable data solutions using data management and modeling best practices using Data Lakes and Cloud data platforms – Snowflake. Uses understanding of the different domain concepts, brokerage services into the data analysis. Deals with complex datasets generated by applications to build and upgrade the data models. Defines use cases and simplifies complex concepts for data quality control. Captures business requirements and translates them to data solutions. Draws on in‑depth knowledge of the business or function to provide business unit‑wide solutions. Primary Responsibilities Develops analytic plans and strategies. Creates and enhances the dimensional data modelling and rule‑based framework. Creates, deploys and maintains the semantic layer between Data model and BI reporting. Conducts highly sophisticated data analysis. Provides guidance and lead the squad to more effective quality data model. Coordinates with stakeholders and cross‑squad team, analysts to represent the squad. Gather requirements, analyze the data architecture and convert it into proper deliverable or made the data engineers to understand and implement. Creates descriptive model and then predictive modelling using AI/ML algorithm. Onboard data consumers to use the deployed data model across enterprise and implement their requirement. Delivers actionable insights to facilitate strategic business planning and decision‑making. Engages in improvements and changes in strategy and business analytics practices in the areas of analytics methodologies, data model structures, and reporting designs. Streamlines data operations and influences the production of reporting and analysis compilation. Identifies, reviews, defines, and interprets work in terms of business and systems requirements and processes. Defines user stories and validates the impact of changes to datasets and models. Manages data quality within an Agile environment. Performs data analysis and profiling. Defines robust test scenarios to deliver scalable and high performing data solutions. Consults on the development and delivery of major technology initiatives for the business unit. Consults on the deployment of major project deliverables. Education and Experience Bachelor’s degree (or foreign education equivalent) in Applied Computer Science, Computer Science, Engineering, Information Technology, Information Systems, Information Management, or a closely related field and three (3) years of experience as a Senior IT Data Analyst (or full stack engineering or closely related occupation) performing data analysis and modeling using SQL, PL/SQL, and Python in a financial and brokerage services domain. Or, alternatively, Master’s degree (or foreign education equivalent) in Applied Computer Science, Computer Science, Engineering, Information Technology, Information Systems, Information Management, or a closely related field and One (1) year of experience as a Senior IT Data Analyst (or full stack engineering or closely related occupation) performing data analysis and modeling using SQL, PL/SQL, and Python in a financial and brokerage services domain. Skills and Knowledge Candidate must also possess: Demonstrated Expertise (“DE”) analyzing, evaluating, and creating data objects for the data models in Oracle SQL, MySQL, PostgreSQL, and Snowflake by transforming the raw data into clean object; performing data wrangling and data visualization using BI tools — PowerBI, tableau, Excel, Jupyter Notebook, and Data studio tools; creating data models using AI /ML algorithms (decision tree model, KNN model, Binary tree model, Linear and Logistic regression data model) with Python and R; deploying ML solutions and publish the descriptive and predictive analysis reports to stakeholders and demonstrate the created data model to data consumer; contributing to the web application consuming data from data model – AngularJS, Spring/Springboot Rest APIs framework. DE quality testing with the ability to write production‑level stored procedure using PL/SQL, JavaScript, and Python adhering to coding standards and best practices; pushing codes and scripts to version control management tools – GitHub and Git Stash; deploying code changes using Continuous Integration/Continuous Delivery (CI/CD) tools — Jenkins and Bitbucket; debugging and tuning complex SQL statements; validating datasets using SQL queries in snowflake, automating the testing with tools ICEDQ and Python scripts; and creating and providing documentation in confluence for Enterprise wide reference. DE working on complex Relational Database Management Systems (RDBMS) and dimensional models to create conceptual, logical, and physical models and data mapping according to standards and best practices, using data modeling tools — SAP Power Designer and Oracle Designer; and delivering scalable and high performing data objects. DE working in agile methodology in partnering within cross‑functional teams, business stakeholders and in creating projects stories, backlogs, and references using enterprise tools — Atlassian, Jira, and Confluence — to execute project deliverables, implementing and automating the requirements from business, design, development, and test stories — according to Agile methodologies. #J-18808-Ljbffr Fidelity Investments Inc.