Keerthika Muthyala

Client : LYONDELL BASELL (Health Care)

Cloud Services: Data bricks, Azure Data Factory, Azure SQL

• Build and maintain ETL/ELT pipelines using Azure Data Factory and Databricks. Automate data ingestion from various sources.
• Utilize PySpark, SQL, and Delta Lake for data transformations. Implement batch and real-time processing.
• Tune queries, optimize partitioning, and monitor pipeline performance.
• Ensure compliance with security policies using encryption, RBAC, and data masking.
• Manage access using Azure AD and service principals.
• Implement DevOps practices using Azure DevOps for automated deployments using CICD
• Collaborate with Power BI and other BI tools to support business reporting needs.
• Work closely with stakeholders to understand business needs and provide documentation.
• Optimized data processing by implementing efficient ETL pipelines and streamlining database design.
• Collaborated on ETL (Extract, Transform, Load) tasks, maintaining data integrity and verifying pipeline stability.

• Projects: SDP Team,DA Sourcing Team,Sybase to Oracle Migration Team , ETL Dev Team, Data Validation Team, PAS Team(Participant Accounting System), NRDE Team
• Clients: PNC Financial Services (Banking Domain), JP Morgan Chase (banking), AXA (Insurance Domain), Baxter (health Care), Moody's Ratings system, Qantas Airways
• Optimized data processing by implementing efficient ETL pipelines and streamlining database design.
• Collaborated on ETL (Extract, Transform, Load) tasks, maintaining data integrity and verifying pipeline stability.
• Enhanced data quality by performing thorough cleaning, validation, and transformation tasks.
• Automated routine tasks using Python scripts, increasing team productivity and reducing manual errors.
• Led end-to-end implementation of multiple high-impact projects from requirements gathering through deployment and post-launch support stages.
• .Fine-tuned query performance and optimized database structures for faster, more accurate data retrieval and reporting.
• Designed data models for complex analysis needs.