Sai Kavyusha Ponnaganti


Data systems built for decisions, not dashboards.

I design and support SQL-based data pipelines and analytics-ready datasets that power operational and business teams. My focus is reliability, clear KPI logic, and data people trust under pressure.

About Me

About Me

Enterprise Data Engineer (Analytics)

SQL Pipelines • Data Quality • Analytics Enablement

I am a Data Engineer with 4+ years of experience working across operational analytics, data engineering, and enterprise reporting systems. My work spans building structured SQL pipelines, validating data quality, documenting transformations, and enabling analytics teams to confidently use production data for decision-making.

I have supported high-volume, SLA-driven environments at companies like Charles Schwab, Citi, Amazon, and Magna Infotech, where data accuracy, consistency, and traceability directly impacted business outcomes.

Systems I've Built

Systems I've Built

Production data systems supporting analytics and operations

Enterprise Analytics Reporting Pipeline

  • Designed and supported SQL-based pipelines transforming raw operational data into analytics-ready datasets.
  • Implemented validation checks for schema consistency, KPI accuracy, and downstream reliability.
  • Enabled self-service reporting for analytics and business teams.

Data Quality & Validation Framework

  • Performed root cause analysis on data inconsistencies across source and reporting layers.
  • Built reconciliation queries to identify defects, missing records, and KPI mismatches.
  • Improved reporting trust through standardized metric definitions.

Operational KPI & SLA Metrics Layer

  • Developed structured KPI datasets tracking SLA adherence, performance trends, and defect rates.
  • Documented metric logic and transformation rules for analytics adoption.
  • Partnered with stakeholders to translate business questions into reliable datasets.
Professional Experience

Professional Experience

Data Engineering • Analytics • Operations

Education

Master's in Data Science

2023 – 2025

DePaul University, Chicago

B.Sc in Mathematics, Statistics & Computer Science

2018 – 2021

Aditya Degree College

Experience

Data Engineer

Aug 2025 – Present

Charles Schwab

  • Designed and supported SQL-based pipelines and reporting datasets used across enterprise teams.
  • Performed data validation, defect analysis, and root cause investigations.
  • Documented transformation logic and metric definitions to improve data trust.

Data Engineer

Jan 2025 – Apr 2025

Citi

  • Supported ETL workflows ingesting structured financial datasets.
  • Wrote SQL for reconciliation, validation, and transformation logic.
  • Assisted with pipeline troubleshooting and lineage documentation.

Seller Partner Support

Apr 2022 – Mar 2023

Amazon

  • Analyzed seller performance, SLA adherence, and defect trends.
  • Built SQL-based reports and dashboards for operational stakeholders.
  • Ensured consistent KPI definitions and reporting accuracy.

Data Engineer

Aug 2020 – Mar 2022

Magna Infotech

  • Built and maintained SQL pipelines supporting business analytics.
  • Performed data validation, reconciliation, and defect analysis.
  • Delivered analytics-ready datasets aligned with operational needs.
Contact

Contact

Open to data engineering and analytics opportunities

Email

saikavyusha@gmail.com

Phone

+1 773-858-9487

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