Akash Birajdar

Data Engineer

ProAzure Software Solutions Pvt. Ltd.

Jan 2021 - Present

Developed real-time data ingestion and processing pipelines to handle high volume banking transaction data from multiple channels. Built PySpark based workflows to transform, enrich and analyze transaction data for near real time fraud monitoring. Integrated customer profiles, account information and transaction history to create a unified dataset for fraud analysis and risk assessment. Developed AI ready feature engineering pipelines to generate customer risk scores and behavioral metrics for fraud detection models. Implemented anomaly detection and fraud monitoring frameworks to identify suspicious transaction patterns and trigger alerts for investigation. Optimized large scale data processing jobs and validation frameworks, reducing processing latency by 35% and improving transaction monitoring efficiency. Developed automated ETL pipelines to extract, transform and load patient, appointment, diagnosis, treatment and billing data from multiple healthcare systems. Integrated and standardized Electronic Health Record (EHR) data from various sources to create a centralized repository for reporting and analytics. Designed SQL based data models, reporting tables and views to support clinical, operational and management reporting requirements. Built interactive Power BI dashboards to analyze patient demographics, treatment outcomes, healthcare utilization, and hospital performance metrics. Implemented data quality validation, reconciliation, and error handling processes to ensure data accuracy, consistency and reliability. Automated data processing and reporting workflows, reducing manual effort and improving report generation efficiency by 40%. Optimized SQL queries and ETL processes to enhance reporting performance and support large scale healthcare datasets. Collaborated with business users and healthcare stakeholders to deliver analytics-ready datasets and actionable insights for decision making. Collected and analyzed inventory, sales and supply chain data from multiple sources using Python and SQL. Developed ETL processes to clean, transform and load inventory data into a centralized database for reporting. Created SQL queries to track stock levels, inventory movement and order fulfillment metrics. Built interactive Power BI dashboards to monitor inventory performance, stock availability, and supply chain KPIs. Performed data analysis to identify inventory shortages, excess stock and demand trends. Automated routine reporting processes, reducing manual effort and improving data accuracy. Generated insights to support inventory planning, procurement decisions, and supply chain optimization. Collaborated with stakeholders to understand reporting requirements and deliver data driven solutions.