Data Engineer with strong foundations in Python, SQL, PySpark, and Power BI,
experienced in building end-to-end data pipelines, transforming raw data into analytics-ready
datasets, and delivering business insights throug…
Data Engineer with strong foundations in Python, SQL, PySpark, and Power BI,
experienced in building end-to-end data pipelines, transforming raw data into analytics-ready
datasets, and delivering business insights through dashboards
<p>Designed ETL data pipelines for replacing client ETL into specific standard framework<br>
Ensured data quality by implementing data validation, cleaning, and transformation<br>
Optimized performance by improving ETL processes, ensuring fast data processing<br>
Collaborated with stakeholders to understand business requirements<br>
Ensured compliance with security and regulatory standards</p>
<p>Built an ETL data pipeline using Python and SQL to analyze retail banking transactions<br>
Processed and transformed customers demographic data<br>
Developed logic and data analytics statistical model to enhance the transaction data<br>
Created Python based metrics for transaction volume, account activity, and branch performance<br>
Developed Power BI dashboards to monitor customer behavior and transaction trends</p>
<p>Developed a data analytics platform to analyze loan applications, repayments, and credit risk indicators<br>
Transformed loan and repayment data using PySpark to track default rates and repayment behavior<br>
Designed SQL based analytics tables for loan performance and risk monitoring<br>
Built Power BI dashboards to visualize loan trends and credit risk metrics</p>
<p>Built an ETL data pipeline to analyze hospital admissions, discharges, and operational efficiency<br>
Cleaned and transformed patient and treatment data using PySpark for analytics reporting<br>
Created Python based metrics to track bed utilization, patient flow, and department performance<br>
Designed Power BI dashboards to support hospital management decision-making</p>
<p>Led and coordinated community service initiatives involving cross-functional student teams<br>
Collaborated with internal and external stakeholders to plan and execute outreach programs</p>
Monitored ETL pipeline runs, handled failures, and resolved performance issues to ensure reliable data processing and ensuring seamless data flow and integration using flask framework, Enhanced tokenization dictionary and composed storage standards for normalized and efficient performance and robustness of built model
Built an ETL data pipeline using Python and SQL to analyze retail banking transactions, Processed and transformed customers demographic data developed logic and data analytics statistical model to enhance the transaction data, Created Python based metrics for transaction volume, account activity, and branch performance, Developed Power BI dashboards to monitor customer behavior and transaction trends
Developed a data analytics platform to analyze loan applications, repayments, and credit risk indicators, Transformed loan and repayment data using PySpark to track default rates and repayment behavior, Designed SQL based analytics tables for loan performance and risk monitoring, Built Power BI dashboards to visualize loan trends and credit risk metrics
Built an ETL data pipeline to analyze hospital admissions, discharges, and operational efficiency, Cleaned and transformed patient and treatment data using PySpark for analytics reporting, Created Python based metrics to track bed utilization, patient flow, and department performance, Designed Power BI dashboards to support hospital management decision-making
Designed ETL data pipelines for replacing client ETL into specific standard framework, Ensure data quality by implementing data validation, cleaning, and transformation, Optimized performance by improving ETL processes, ensuring fast data processing, Collaborated with stakeholders to understand business requirements, Ensure compliance with security and regulatory standards
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