Krithika Shankar

Senior Analytics Developer (L5) @Kinaxis

Led a team of analysts and partnered with data scientists, data engineers and product management team to design data modelling requirements for building robust demand forecasting solution-Designed scalable normalized data model in Databricks and configured automated ETL pipelines using YAML & SQL to transform source data from external platforms like AWS Redshift and GCP.[Azure Databricks]-Tuned SQL queries to improve runtime performance of ETL transformational logics by 40% and implemented optimal table partitioning strategies during data ingestion thereby reducing query time by 60%.[SQL]-Built a data quality assessment module integrated with ETL workflows with custom business rule validations to flag data issues and schema inconsistencies leading to effective reduction in forecast MAPE by 10%-Led product enhancement effort in implementing a sales explainability dashboard enabling category management to analytically quantify impact of internal and external drivers of promotional demand.[SQL, PySpark, PowerBI]- Implemented an improved methodology to capture ““actual stock out rate” feature by analyzing product inventory and sales data along with forecasted demand thus reducing error rate in capturing “missed sales” by 5%.[PySpark]