Sandhya G.
Sr Azure Data Engineer @BMW Toronto
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WORK HISTORY
Sr Azure Data Engineer @BMW Toronto
Toronto, ON, CA
Designed scalable ETL pipelines using Azure Data Factory for healthcare claims, reducing ingestion time and boosting efficiency.Built and automated end-to-end data pipelines with ADF and Databricks for large-scale analytics.Developed high-performance data transformations using Apache Spark, PySpark, Scala, and R for batch and real-time processing.Optimized batch workflows using Spark and ADF, reducing execution times significantly.Leveraged Hadoop (HDFS, Hive, YARN) for scalable data storage and processing.Managed structured/unstructured data in Azure Blob Storage with a focus on performance and security.Implemented enterprise data warehousing solutions via Azure Synapse Analytics.Created ETL workflows for claims processing and patient stratification using ADF and Spark.Built event-driven solutions using Azure Functions and Logic Apps for automation.Integrated SQL/NoSQL databases: SQL Server, PostgreSQL, MySQL, MongoDB.Applied RBAC policies and security best practices for Azure IAM governance.Ensured HIPAA compliance with secure data handling and encryption.Developed real-time ingestion pipelines using Kafka, NiFi, and Flume.Built Power BI dashboards for claims analytics and patient engagement.Integrated Salesforce CRM data to drive customer insights.Automated batch processes using ADF, Spark, and Informatica PowerCenter.Deployed containerized data solutions using Docker and Kubernetes.Used SharePoint and OneDrive for secure collaboration.Wrote complex SQL/PLSQL queries for data extraction and reporting.
EDUCATION
JNTUH College of Engineering Hyderabad
Bachelor of Technology, Computer Software Engineering
ABOUT SANDHYA G.
Application Support Analyst with experience in capital markets, FX trading operations, andenterprise data platforms. Strong background in incident management, SQL-based analysis,system integrations, and release coordination. Skilled at supporting business-critical applications,documenting workflows, and working closely with technology teams, vendors, and to maintain stable and accurate system performance
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