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Sreenija Karnati
Mid-level Data Analyst and Data Engineer specializing in healthcare and financial analytics
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About
Analytics professional with healthcare and operations experience who turns messy enterprise data from platforms like Teradata, GCP, SQL Server, and Snowflake into trusted reporting layers and reproducible analysis workflows. They combine SQL, Python, PySpark, Power BI, and Tableau to improve reporting accuracy and performance, including a 30% dashboard refresh improvement and 20-25% accuracy gains in healthcare reporting.
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Key Strengths
- Built SQL pipelines to standardize messy multi-source healthcare data for BI reporting
- Strong data quality remediation across duplicates, mismatched values, and delayed/incomplete records
- Validated analytics outputs with source-to-curated aggregate checks, manual sampling, and edge-case testing
- Improved dashboard refresh performance by about 30%
- Improved reporting accuracy by 20-25% through validation checks and duplicate handling
- Automated reproducible Python analytics workflows using Pandas, NumPy, and PySpark
- Delivered operational insight from backorder analysis, identifying 30% of delays from supplier lead times and inventory issues
- Owned end-to-end analytics projects from metric definition through stakeholder alignment and dashboard delivery
- Operationalized standardized business metrics in SQL and Power BI to drive stakeholder adoption
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