Discover and understand business requirements from a BI context in order to design, implement, and continuously expand data pipelines for reporting by performing:• Data extraction, using Python specific data-analys libraries(including but not limited to Pandas, Numpy, Sqlalchemy) to automate raw data extraction from various sources(included but not limited to: email, client reporting systems, web, flat files). This step might also include SQL queries.• Data transformation of raw data… Show more Discover and understand business requirements from a BI context in order to design, implement, and continuously expand data pipelines for reporting by performing:• Data extraction, using Python specific data-analys libraries(including but not limited to Pandas, Numpy, Sqlalchemy) to automate raw data extraction from various sources(included but not limited to: email, client reporting systems, web, flat files). This step might also include SQL queries.• Data transformation of raw data by analyzing, processing, transforming and consolidated for its intended analytical use case(this might include filtering, cleansing, de-duplicating, validating, and authenticating the data). Design the data model using specific data-modelling methodologies like star-schema or snowflake schema. • Data loading, including identifying the storage needs for the data warehouse and building it accordingly with the data-modelCreate dashboards and interactive visual reports using Power BI. This might include creating relationship between data, additional data-transformation using Power Query engine, performing DAX queries.Providing maintenance and documentation for everything designed above. Show less

• Performing analysis by exploring past staffing trends and customer demand and then using projections to develop schedules on a daily to monthly basis. • Providing recurrent and ad-hoc reports(containing performance data to support operations management)on a variety of metrics including daily agent statistics and skill group/call type statistics; analyzing data to identify trends, issues, and opportunities, and uncovering levers impacting these issues, and developing recommendations for… Show more • Performing analysis by exploring past staffing trends and customer demand and then using projections to develop schedules on a daily to monthly basis. • Providing recurrent and ad-hoc reports(containing performance data to support operations management)on a variety of metrics including daily agent statistics and skill group/call type statistics; analyzing data to identify trends, issues, and opportunities, and uncovering levers impacting these issues, and developing recommendations for improvement.• Analyze agent schedule performance(on individual and site level)and accuracy of the forecast for making continuous adjustments on headcount planning and scheduling process to make sure service levels are met. Show less