Dharma V

● Results-driven and detail-oriented Azure Data Engineer with 3.7 years of professional experience in designing, building, and optimizing data pipelines and ETL processes using Azure Data Factory, Azure Databricks, and PySpark .

● Proficient in Python scripting, SQL Server developmentand integrating on-premise and cloud data sources for scalable data solutions.

● Strong expertise in Data Warehousing, Data Modeling, and developing robust ETL frameworks to support analytical and operational reporting needs.

● Experienced in implementing business intelligence solutions using Power BI, SSIS, and SSRS to deliver insights and data visualizations across business units.

● Proficient in developing and automating end-to-end data pipelines on Azure using ADF and Databricks, integrating various structured and unstructured data sources.

● Hands-on experience in writing scalable and optimized PySpark code for large-scale data processing and implementing data transformation logic.

● Strong skills in Python for data ingestion, automation scripts, and integration with cloud services.

● Designed and implemented ETL workflows using Azure Data Factory, SSIS, and Databricks, ensuring timely data availability for business-critical applications.

● Expertise in Data Modeling (Star & Snowflake Schema) and designing scalable Data Warehouse solutions on Azure SQL and Synapse Analytics.

● Strong command over SQL Server including development of T-SQL scripts, stored procedures, functions, views, and performance tuning.

● Experience in developing interactive dashboards and reports in Power BI, enabling stakeholders to derive actionable insights.

● Developed SSRS reports for operational and analytical reporting requirements and integrated them into business systems.

● Built and maintained SSIS packages for data extraction, transformation, and loading from various data sources like flat files, Excel, SQL Server, and REST APIs.

● Knowledge of CI/CD pipelines, version control (Git), and integration with Azure DevOps for deployment automation.

● Strong understanding of data governance, security, logging, and monitoring in a cloud environment.

● Collaborated closely with business analysts, data scientists, and end-users to understand data needs and deliver value-added solutions.

● Experience with incremental loads, data partitioning, delta lake tables, and performance tuning in Databricks.

● Adept in troubleshooting data issues, performing root cause analysis, and implementing effective resolutions.

● Good understanding of Spark Architecture, Transformations and Actions.

● Excellent knowledge of ADF building components – Integration Runtime, Linked Services, Data Sets, Pipelines, Activities.