Praneetha Kotta
Data professional with over 3 years of experience in data analysis, data integration, validation, and reporting
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About
Data professional with over 3 years of experience in data analysis, data integration, validation, and reporting across consulting and ERP environments. Proficient in SQL, Python, PySpark, Hadoop, Hive, Power BI, and Tableau, with hands-on experience building ETL workflows, data-quality checks, reconciliation scripts, KPI dashboards, and cross-system integrations involving Oracle ERP and Salesforce. Demonstrated ability to improve reporting efficiency, pricing accuracy, transaction performance, and data reliability through automation and analytical solutions.
Experienced in working with large datasets, dimensional modelling, data warehousing, and translating complex business requirements into accurate, decision-ready insights.
Experience
Data Analyst Intern - Sysnous Consulting - UK
(2024-05 - 2025-05)
- Built batch and incremental Azure Data Factory pipelines to ingest ERP data into Azure Data Lake Storage Gen2.
- Transformed ERP datasets using Azure Databricks, Python and PySpark, loading reporting-ready data into Azure SQL Database.
- Used SQL to extract, join, aggregate and prepare ERP data for KPI reporting and Power BI dashboards.
- Developed Python validation scripts to reconcile record counts, transaction totals, identifiers, nulls and duplicates.
- Used pytest, Docker and CI/CD to automate testing and support consistent deployment of data-processing scripts.
- Developed Power BI dashboards that reduced reporting preparation time from five to four hours, improving turnaround by 20%.
DC Analyst - Deloitte Consulting - India
(2021-03 - 2023-05)
- Designed SQL-based validation workflows to process subscription and pricing datasets across Salesforce and Oracle ERP systems, improving pricing accuracy by 28%.
- Built automation scripts to streamline bulk data uploads and reduce configuration errors.
- Engineered API driven data integration workflows ensuring consistent cross-system data synchronization.
- Optimised rule-processing and data transformation logic, reducing transaction latency by 35% in high-volume quoting environments.
- Improved cross system data routing and attribute mapping between CPQ, OCC, and ERP platforms, driving 99% transaction accuracy.
Education
MSc - Computing (Data Analytics) - Sheffield Hallam University (2023-09 - 2025-09)
