Amrita Kumari

Designed and implemented scalable data architectures for internal IBM projects. Conducted detailed architecture reviews and mentored team members in advanced data engineering methodologies.

Built and optimized end-to-end data pipelines and KPIs for profit share calculations, reducing processing time by 20%. Developed interactive dashboards using Power BI and Azure tools, enhancing data visibility for stakeholders. Designed data models and implemented ETL workflows to manage and transform high-volume datasets while ensuring data quality and governance.

Developed scalable ADF pipelines for ESG requirements, increasing process automation by 40%. Utilized Azure Databricks and PySpark to address complex business needs, improving data processing reliability.

Engineered ETL pipelines with Spark, improving data ingestion efficiency. Automated data validation processes using Python, reducing manual effort. Migrated large datasets from HDFS to Redshift and optimized Spark-Scala applications using best coding practices. Prepared comprehensive technical design documents and analysed change requests for seamless implementation.

Designed and automated data pipelines for high-priority business requirements, ensuring timely delivery. Enhanced reporting accuracy by developing robust ETL inventories and data dictionaries. Resolved critical production issues and transitioned knowledge effectively to operations teams.

Migrated extensive relational data from SAP tables to HDFS, ensuring seamless data accessibility. Developed Hive scripts and shell automation for centralized data retrieval, reducing query time significantly. Automated data synchronization workflows using HDF strategies, improving operational efficiency by 35%.