---
title: "Divyank Chaudhary - Data Analyst in India | Tal"
description: "Meet Divyank Chaudhary, Data Analyst | SQL, Snowflake & dbt | Python | Data Pipelines & ETL | Apache Airflow | Power BI & Data Visualization | Data Quality & Analytics| Immediate Joiner based in India. AI stack includes claude, github copilot, and openai. Explore public work links including github."
image: "https://tal.club/meet/divyank-chaudhary/share-image"
---

# Divyank Chaudhary on Tal

## Headline

Data Analyst \| SQL, Snowflake & dbt \| Python \| Data Pipelines & ETL \| Apache Airflow \| Power BI & Data Visualization \| Data Quality & Analytics\| Immediate Joiner

## About

Data Analyst with 5\+ years of experience across data analytics, energy and commodities research, data pipelines, and business intelligence at Wood Mackenzie and S&P Global\. I specialise in transforming complex, fragmented datasets into reliable, analytics\-ready data products that support research, forecasting, reporting, and business decision\-making\. My experience spans SQL\-based transformations, Snowflake data platforms, dbt modelling, pipeline orchestration, data validation, and interactive BI dashboards\. Key highlights: 1B\+ records migrated from AWS S3 and Athena to Snowflake using a medallion architecture and dbt models\. Reduced time spent on source\-table changes by 60%\+ by enabling researchers to update source data through a streamlined CSV ingestion workflow\. Implemented 30\+ automated data quality and validation checks to improve data accuracy, completeness, and reconciliation\. Reduced asset\-selection time for modelling by 50%\+ through a centralized Apache Superset dashboard\. Improved chatbot reliability to 90%\+ by validating responses against source data using SQL in Databricks\. Built 5\+ interactive Power BI dashboards to support reporting and analytics\. Technical expertise Data Analytics: SQL, Python, Pandas, NumPy, exploratory data analysis, statistical analysis, and data validation\. Data Engineering: Snowflake, dbt, Apache Airflow, AWS S3, Amazon Athena, Databricks, ETL pipelines, and medallion architecture\. BI & Visualisation: Power BI, Apache Superset, Tableau, and Advanced Excel\. Analytics & Forecasting: Logistic Regression, Decision Trees, ARIMA, trend analysis, and model evaluation\. Engineering Practices: Git, pull requests, code reviews, and version\-controlled development\. With a postgraduate degree in Economics from the Delhi School of Economics, I bring a combination of analytical thinking, business understanding, and technical execution\. My experience in energy and commodities research helps me connect data workflows with practical business and research requirements\. I enjoy building dependable data systems, improving data quality, automating repetitive processes, and enabling stakeholders to make better\-informed decisions\. Core technologies: SQL \| Snowflake \| dbt \| Python \| Apache Airflow \| Power BI \| AWS \| Databricks

## Location

India

## AI stack

claude

github copilot

openai

githubcopilot

ChatGPT

Microsoft Copilot

## Work experience

Data Analyst at Wood Mackenzie, Apr 2025 \- Present · 1 yr 8 mos, Gurugram, \- Migrated data pipelines from AWS S3 and Amazon Athena to Snowflake, processing 1B\+ records through bronze, silver, and gold layers using event\-based ingestion and six dbt models to power client dashboards\. \- Developed a CSV\-based ingestion workflow enabling researchers to update source data independently, reducing time spent on table changes by 60%\+ and minimizing Engineering dependencies\. \- Orchestrated Snowflake data models using Apache Airflow, scheduling, monitoring, and troubleshooting migration workflows while maintaining data integrity through Git\-based pull requests and code reviews\. \- Implemented 30\+ automated data quality checks covering accuracy, completeness, and reconciliation to improve the reliability of asset data used in dashboards and forecasting models\. \- Built a centralized Apache Superset dashboard on the gold data layer to track asset readiness across generation, market prices, and installed capacity, reducing researchers’ asset\-selection time for modelling by 50%\+\.

Data Analyst at S&P Global, Dec 2023 \- Apr 2025 · 1 yr 5 mos, Hybrid, \- Validated chatbot responses against source data using SQL in Databricks, improving chatbot reliability to 90%\+\. \- Established a Snowflake–Power BI integration and developed 5\+ interactive dashboards, using SQL\-based transformations to support business reporting and analytics\. \- Automated the collection and centralization of vessel\-tracking data for 100\+ vessels, enabling downstream modelling and reporting\. \- Consolidated recurring country\-level market datasets and delivered structured data to Snowflake for downstream analytics and reporting\.

Consulting Analyst at S&P Global, Jul 2021 \- Nov 2023 · 2 yrs 5 mos, Gurugram, \- Developed a supply\-demand model for the alternative protein market to evaluate market evolution, potential supply\-demand gaps, and emerging opportunities\. \- Analyzed confectionery manufacturing costs to assess the implications of shifting seven production units from the US to Brazil\. \- Evaluated feedstock data across vegetable oils, beef, poultry, and sheep to assess the potential of used cooking oil as a low\-carbon biofuel in Pakistan\.

## Education

Master's degree, Economics, Delhi School of Economics

Bachelor of Arts, Economics, Hindu College, University of Delhi

## Public links

- github: https://github\.com/divyankc7

[View the original profile](https://tal.club/meet/divyank-chaudhary)

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