Priyanka Talluri

Led development of Python-based GenAI architectures integrating LLMs, solving complex unstructured financial text challenges with a 35% accuracy improvement. Architected normalized SQL data pipelines processing 10 million daily records, ensuring seamless flow into embedding and LLM workflows for downstream applications. Established cross-team data pipeline standards that improved coordination betw

Designed and deployed 30+ interactive dashboards in data-bricks enabling leadership to monitor KPIs related to transaction volumes, partner onboarding, and operational efficiency across Platform Solutions.
• Analyzed and modeled large datasets from Snowflake and AWS Redshift, providing insights that led to the streamlining of payment workflows and a 25% reduction in processing delays.
• Built and

At Goldman Sachs, I played a pivotal role as a Data Engineer, where I transformed data workflows by integrating Kafka with Snowflake. My responsibilities included managing data pipelines and utilizing Airflow for orchestration. I also focused on maintaining platform efficiency through systematic cleanup processes.

• Analyzed student lifecycle and academic performance data using SQL and Python, building predictive models to forecast dropout risk with 85% accuracy.
• Built Power BI dashboards to visualize trends in retention, program enrollment, and instructional resource utilization, improving decision-making by academic leadership.
• Automated ETL workflows using Python and Excel macros to aggregate dataset

Developed Python and SQL automated reporting dashboards, reducing manual report generation time by 40% and improving operational visibility. Architected SQL data marts with optimized schema profiling, accelerating data access for exploratory analysis by 25%. Standardized Python-based ETL processes across departments, streamlining workflows and cutting manual effort by 30%. Implemented Git version

• Developed and optimized T-SQL and PL/SQL queries, functions, and stored procedures for data warehousing projects in the BFSI (Banking & Financial Services) sector.
• Automated recurring reporting tasks using SQL Agent Jobs and Excel VBA macros, improving efficiency across finance and audit teams.
• Built ad hoc reports and data extracts for clients using parameterized queries and dynamic SQL in

• Automated end-to-end ETL workflows using Python (pandas, os, csv, glob) for cleansing and transforming datasets from various sources into relational databases.
• Applied data validation logic and custom functions to standardize and clean high-volume transactional data, reducing manual cleanup time.
• Developed in-house visual reporting tools using matplotlib and seaborn to monitor performance me

• Supported senior developers in building SQL queries for customer segmentation and KPI dashboards used by operations and marketing teams.
• Created Excel-based summary reports with VBA automation, improving consistency and turnaround of weekly deliverables.
• Participated in UAT testing of ETL processes and collaborated with QA to validate mappings, formats, and target loads.
• Documented data lo

Issued Jan 2025

Issued May 2024