Akhil Kumar

<p>Designed and developed end-to-end ETL pipelines in Azure Data Factory (ADF) to ingest data from APIs, flat files, and on-prem SQL servers into Azure Data Lake Storage (ADLS).</p><p> Built parameterized and metadata-driven ADF pipelines to support reusable, scalable, and automated data integration processes across multiple healthcare data sources.</p><p> Developed PySpark notebooks in Azure Databricks to perform data cleansing, transformation, and business rule implementation for large healthcare datasets.</p><p> Created and maintained Delta Lake tables in Azure Databricks to provide reliable, ACID-compliant storage for structured and semi-structured healthcare data.</p><p> Optimized Databricks jobs by implementing partitioning, caching, and performance tuning techniques, resulting in faster data processing and reduced execution time.</p><p> Integrated Azure Synapse Analytics with curated datasets to support analytical reporting, ad-hoc SQL queries, and downstream business intelligence requirements.</p><p> Developed robust data validation, logging, and exception handling mechanisms in ADF and Databricks to improve data quality and monitor pipeline failures.</p><p> Processed high-volume patient, provider, claims, and clinical datasets using PySpark, ensuring data consistency and adherence to healthcare business requirements.</p><p> Managed data organization in ADLS Gen2 by implementing optimized folder structures, partitioning strategies, and lifecycle management for efficient storage utilization.</p><p> Collaborated with Data Scientists, Business Analysts, and Reporting teams to deliver curated datasets for Machine Learning, predictive analytics, and operational reporting.</p><p> Secured sensitive healthcare data using Azure Key Vault, Managed Identity, and Role-Based Access Control (RBAC) to meet organizational security standards and HIPAA compliance requirements.</p><p> Published curated datasets to Azure Synapse Analytics and integrated them with Power BI to develop interactive dashboards for patient insights, claims analysis, and healthcare performance reporting.</p><p> Worked with Microsoft Fabric Lakehouse to centralize curated healthcare datasets and support enterprise-wide analytics and reporting.</p><p> Developed Microsoft Fabric Data Factory pipelines and Dataflows Gen2 to automate data ingestion, transformation, and orchestration across multiple healthcare systems.</p><p> Integrated Microsoft Fabric Lakehouse with Power BI to deliver self-service reporting solutions, enabling business users to analyze healthcare data through interactive dashboards.</p><p> Implemented incremental data loading using Watermarking and Change Data Capture (CDC) to reduce processing time and improve pipeline efficiency.</p>

<p>Designed and developed ETL Pipelines in Azure Data Factory (ADF) for Batch and Incremental Data Ingestion from diverse Data Sources.</p><p> Built and optimized Data Transformation Workflows using Azure Databricks with PySpark for Large-Scale Data Processing.</p><p> Implemented Data Lake Architecture on Azure Data Lake Storage Gen2 (ADLS Gen2) to store Raw, Curated, and Consumption-Ready Datasets.</p><p> Developed and tuned complex SQL Server Queries, Stored Procedures, Functions, and Triggers for Transactional and Analytical Processing.</p><p> Integrated ADF Pipelines with Azure Databricks Notebooks for seamless Data Transformation and Workflow Orchestration.</p><p> Created Data Models in SQL Server and Azure Synapse Analytics to support Business Intelligence (BI) and Analytics Solutions.</p><p> Designed and implemented Parameterized Pipelines, Triggers, and Linked Services in Azure Data Factory (ADF) for Automation and Reusability.</p><p> Performed Data Migration from On-Premises SQL Server to Microsoft Azure using Azure Data Factory (ADF), Azure Databricks, and Azure Data Lake Storage Gen2 (ADLS Gen2).</p><p> Developed Power BI Dashboards and Reports integrating with SQL Server and Azure Synapse Analytics for Self-Service Analytics.</p><p> Applied Data Security and Data Governance best practices including Role-Based Access Control (RBAC) and Data Encryption.</p><p> Collaborated with Cross-Functional Teams to deliver End-to-End Data Solutions for Business Intelligence (BI) and Analytics.</p><p> Monitored, debugged, and optimized ADF Pipelines, Apache Spark Jobs, and SQL Queries to improve Performance, Scalability, and Cost Optimization.</p>

<p>Analyzed source data and understood business requirements to develop reporting solutions.</p><p> Generated Weekly, Monthly, Quarterly, and Yearly Reports to support business decision-making.</p><p> Used Page-Level Filters and Report-Level Filters to create interactive visualizations in Power BI.</p><p> Gathered and analyzed business requirements to identify reporting and system needs.</p><p> Imported data from SQL Server into Power BI Desktop using the Get Data option.</p><p> Performed data analysis using SQL with SELECT, Aggregate Functions, and GROUP BY statements.</p><p> Developed multiple Scorecards, Reports, Visualizations, and Interactive Dashboards using Power BI Desktop.</p><p> Configured Scheduled Refresh and managed Automatic Data Refresh in Power BI Service.</p><p> Developed analytical reports using DAX Functions, including Table Functions, Aggregation Functions, and Iterator Functions.</p><p> Created reports using Time Intelligence Functions for daily, monthly, quarterly, and yearly business analysis.</p><p> Designed customized and interactive reports and dashboards to meet business reporting requirements.</p><p> Published reports to Power BI Service and managed user access and workspace permissions.</p>