Jangam Ramyasri

I’m an Azure Data Engineer with ~3 years of experience designing scalable data pipelines on Azure Data Factory, Azure Databricks, and ADLS Gen2. I specialize in building ETL/ELT pipelines that move data reliably from ERP systems, APIs, SQL databases, and CSV sources into analytics-ready storage.

In my role at Tata Consultancy Services (TCS), I built batch and incremental loading strategies that reduced overall data processing time by 30%. I implement PySpark transformations in Azure Databricks to process and cleanse large-scale datasets, and I use Delta Lake architecture with partitioning strategies to improve performance and ensure reliable storage.

I also design curated data models for analytics workloads using Star Schema and Snowflake Schema in Azure Synapse Analytics. I’ve implemented SCD Type 1 and Type 2 logic to manage historical and incremental changes, and I’ve delivered optimized datasets that power Power BI dashboards for enterprise reporting and business decision-making.

I take a strong engineering approach to security, observability, and maintainability—integrating Azure Key Vault for secure credential management and configuring monitoring with Azure Monitor and Log Analytics to meet SLA requirements. I enjoy building dynamic, parameterized pipelines and automating executions to improve accuracy, reduce manual effort, and scale to 10+ data sources.