Bhavya Prudhvi Teja Kolla

• Worked on Creating and maintaining optimal data pipeline architecture.
• Developing complex SQL queries, query optimization, data analysis, database management and reporting.
• Created an agile working environment, enabling rapid response to changing business needs without sacrificing quality or performance standards.
• Developing data visualization reports and dashboards using Power BI and Tableau.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Designing ETL and building data pipelines that clean, transform, and aggregate data from disparate sources.
• Involved in interacting, communicating, and presenting with both business and technical teams.
• Hands on experience with AWS services including Cloud Formation, EC2, EMR, IAM, KMS, Lambda, RDS, and S3.
• Working with Git code base repository Proficiency in Python.
• Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies.

• Designed, developed, and overhauled a real-time lead prioritization predictive model to process data of existing customers and new prospects using dbt, snowpark
• Led end-to-end architecture on modern ELT data stack on dbt core and snowflake
• Reduced manual and hands-on tasks by 40+ hours per request by creating a tool that obtained data and created documentation using Python, GraphQL, REST APIs, and AWS Lambda
• Migrated and refactored complex Alteryx data pipelines using dbt, creating a more efficient approach to reverse ETL Salesforce data leading to a significant reduction in tech debt and enabling the team to build relevant and actionable KPIs and metrics
• Developed incremental and snapshot dbt models in snowflake, and orchestrated CI/CD data pipelines, which reduced the ELT run time from +12 hours to less than 20 minutes
• Engineered a python automation script that enabled the internal analytics team to reduce maintenance tasks on the Tableau server by 75%

• Reengineered existing ETL workflows to improve performance by identifying bottlenecks and optimizing code accordingly.