Product Data Analyst - SQL, Python, Snowflake Expert

Kapil Vardhan Ayenala Product Data Analyst

West Haven, CT +1-203-***-**** *************@*****.*** LinkedIn Summary

Data Analyst with 3+ years of experience leveraging SQL, Python, and Snowflake to optimize fulfillment, pricing, and operations for e- commerce platforms. Skilled in data pipelines, forecasting, and experimentation, with a track record of translating analytics into measurable growth and efficiency improvements.

Skills

• Data Analytics & Visualization: Tableau, Power BI, Looker, Excel, PowerPoint, Data Storytelling, KPI Design, Dashboard Automation

• Programming & Data Science: Python (pandas, NumPy, scikit-learn, XGBoost, matplotlib, seaborn), R (tidyverse), SQL (MySQL, Snowflake, BigQuery, Redshift)

• Data Engineering & Pipelines: dbt, Airflow, ETL/ELT Design, Data Modeling, Data Warehousing, API Integration, CI/CD (Git, GitHub)

• Machine Learning & Experimentation: Predictive Modeling, Forecasting, Uplift Modeling, Regression Analysis, Clustering, A/B Testing (t-tests, significance testing), Model Validation (MAE, RMSE, Backtesting)

• Cloud & Big Data Platforms: AWS (S3, Lambda), GCP (BigQuery, Cloud SQL), Azure (Data Factory), Snowflake

• Data Governance & Collaboration: Data Quality Validation, Metric Standardization, Stakeholder Alignment, Agile Scrum, Jira, Confluence Professional Experiences

Product Data Analyst Instacart USA Feb 2025 - Present

• Collaborated with three product pods to diagnose routing inefficiencies across Instacart’s fulfillment network, improving slot allocation logic and reducing order cancellations by 9%.

• Designed and deployed data pipelines using Snowflake, dbt, and Airflow to process 10TB+ of daily order and fulfillment data, improving reliability and cutting refresh latency by 40%.

• Overhauled KPI definitions and governance processes for fulfillment and SLA tracking, improving data consistency, and enabling unified reporting across Product and Operations.

• Developed forecasting and uplift models in Python using scikit-learn and XGBoost; validated performance through backtesting (MAE, RMSE) to enhance promotional demand prediction by 18%.

• Conducted A/B testing on pricing experiments, instrumenting event tracking in product logs and using SQL with t-tests (95% CI) to identify variants that increased conversion by 12%.

• Partnered with cross-functional teams PMs, Data Engineers, and Operations to align analytics priorities, manage Airflow DAG versioning in Git, and support Agile sprint deliverables.

• Initiated fulfillment metrics governance to standardize KPI definitions across regional teams and improve executive reporting consistency. Instructional Assistant (Analyst) University of New Haven USA Jun 2024 - Feb 2025

• Supported institutional analytics initiatives by building automated Excel and Python workflows to process 2K+ grade records, improving reporting turnaround by 25%.

• Built interactive Power BI dashboards to track student performance and equity trends, enabling faculty to identify and support at-risk learners early.

• Analyzed and optimized project resource allocation and infrastructure costs, implementing forecasting workflows that improved budget accuracy and reduced operational overhead

• Applied statistical validation techniques (variance, correlation, z-scores) to evaluate question difficulty and ensure fair assessment design.

• Collaborated with professors to analyze learning outcome data and adjust pacing, improving average course performance by 8%.

• Streamlined data validation and reporting processes, ensuring transparency and academic integrity across assessments. Data Analyst Tudip Technologies India Aug 2022 - Jul 2023

• Revamped Tableau dashboards for SLA and defect tracking, creating a unified view for QA and Engineering teams that were adopted by six client projects to enhance sprint analytics.

• Engineered SQL automation scripts in MySQL processing 100K+ issue logs per month, reducing manual reporting cycles by 30%.

• Performed root-cause and trend analyses with Python (pandas, matplotlib) to uncover recurring defects, driving a 15% reduction in issue of recurrence.

• Implemented a standardized KPI framework for release quality, improving visibility, alignment, and collaboration across Agile teams via Jira and Confluence.

• Presented defect insights and sprint performance findings to stakeholders, influencing prioritization and roadmap planning.

• Mentored two junior analysts on SQL query optimization and dashboard-building best practices. Education

Master of Science in Business Analytics University of New Haven, Connecticut, US Dec 2024 Bachelor of Technology in Electronics and Communications Anil Neerukonda Institute of Technology & Science, India May 2022

Contact this candidate