center. Key Responsibilities: + Data Analysis: Analyze contact center performance data to identify trends, patterns, and opportunities for improvement. + Dashboard Development: Create and maintain interactive dashboards in PowerBI, Looker & CUIC to provide actionable insights for leadership. + Reporting: Generate regular and ad-hoc reports to support decision-making processes. + Data Integration: Work with CUIC, CVP, ICM, and Google DialogFlow data sets. Proficient in integrating and harmonizing disparate datasets across multiple data warehouses, including Enterprise Data Warehouse (EDW), Google BigQuery, and Databricks. + Collaboration: Work closely with cross-functional teams to understand data needs and deliver solutions that meet business requirements. + Quality Assurance: Ensure data accuracy and integrity through rigorous validation and testing processes. + Proactive Problem Solving: Identify and address data-related issues promptly and effectively. Qualifications: + Education: Bachelor's degree in Data Science, Computer Science, Statistics, or a related field. + Experience: Minimum of 5 years of experience in data analysis, with a focus on contact center data. Technical Skills: + Proficiency in PowerBI, Tableau, CUIC and Looker Studio for report/dashboard creation. + Advanced Proficiency in SQL and Data Manipulation: + Complex Querying: Expertise in writing and optimizing complex SQL queries, including the use of subqueries, Common Table Expressions (CTEs), and window functions to perform advanced data analysis + Data Transformation: Skilled in transforming and reshaping data using techniques such as pivoting and unpivoting, which allow for better analysis and reporting + Performance Tuning: Proficient in optimizing query performance through indexing, query plan analysis, and other SQL performance tuning techniques + Stored Procedures and Triggers: Experience in creating and managing stored procedures and triggers to automate repetitive tasks and ensure data integrity + Data Integration: Capable of integrating data from multiple sources and ensuring consistency and accuracy across datasets + Error Handling and Debugging: Strong ability to handle errors and debug complex SQL queries to ensure accurate and reliable data outputs + Advanced CASE Expressions: Proficient in using advanced CASE expressions for complex conditional logic and data categorization + Data Security: Knowledgeable in implementing data security measures within SQL, including user permissions, data encryption, and secure data handling practices + Familiarity with programming languages such as Python or R is a plus, for Machine Learning and Predictive Analytics to access to ML Libraries and Predictive Modeling.