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Shashi Kumar Malothu

@shashikumarmalothu

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I automate financial reporting and build data-driven dashboards using SQL, Power BI, Excel, and Azure Data Factory.

United States

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At the New Mexico Department of Health, I automate general ledger reconciliation with SQL, build Power BI dashboards for specific stop loss claims, and analyze budget variances to support regulated financial operations.

Previously at Dell Technologies, I improved budget accuracy by 25% through SQL forecasting models and reduced manual reporting effort by 30% with Excel macros and VBA. I also orchestrated Azure Data Factory ETL pipelines and delivered KPI reporting for stakeholders.

I began as a Data Analyst Intern at Cognizant, where I used SQL, Python, Excel, and Power BI to clean data, automate recurring tasks, identify reporting variances, and improve reporting reliability.

Experience

Work history, roles, and key accomplishments

Current

Financial Analyst

Current

New Mexico Department of Health

Oct 2025 - Present (1 year 1 month)

Automated general ledger reconciliation using SQL, improving data preparation accuracy for claim entry by 20% and reducing manual matching time significantly. Designed Power BI dashboards tracking specific stop loss claim data, enabling leadership to access real-time insights and improve decision-making speed by 30%.

SQL Power BI SAP FI CO Variance Analysis Root Cause Analysis Data Preparation Dashboarding Process Automation

Financial Analyst

Dell Technologies

Jan 2022 - Dec 2023 (1 year 11 months)

Developed forecasting models using SQL that improved budget accuracy by 25%, enabling more reliable financial planning in a regulated environment. Automated repetitive reporting processes with Excel macros and VBA, reducing manual effort by 30% and accelerating monthly close cycles.

SQL Excel VBA Macros Power BI Azure Data Factory ETL Predictive Analytics Variance Analysis Root Cause Analysis KPI Tracking Stakeholder Reporting

Data Analyst Intern

Cognizant

Jan 2021 - Dec 2021 (11 months)

Extracted large datasets using SQL and prepared data by standardizing formats and cleaning inconsistencies to support accurate claim entry processes. Automated repetitive data cleaning tasks with Python scripts and Excel macros, improving team efficiency by 22% and reducing manual errors.