---
title: "Abhishek Chavan - Data Engineer in Mumbai Metropolitan Region | Tal"
description: "Meet Abhishek Chavan, Data Engineer | Azure Databricks · ADF · PySpark · SQL | Building Scalable ETL Pipelines | 3.6 Yrs @ Cognizant | Open to Opportunities based in Mumbai Metropolitan Region. AI stack includes gemini, langchain, and ollama."
image: "https://tal.club/meet/abhishek-61/share-image"
---

# Abhishek Chavan on Tal

## Headline

Data Engineer \| Azure Databricks · ADF · PySpark · SQL \| Building Scalable ETL Pipelines \| 3\.6 Yrs @ Cognizant \| Open to Opportunities

## About

I build data pipelines that actually scale — and then make them faster\. As a Data Engineer at Cognizant, I've spent 3\.6 years designing and optimizing ETL workflows that process 1M\+ records daily using Azure Databricks, ADF, and PySpark\. I don't just move data — I cut reporting latency by 30%, automated batch workflows to reduce execution time by 80%, and built a custom ingestion framework that saved $800/month in infrastructure costs\. My stack: Azure Data Factory · Databricks · Apache Spark · PySpark · SQL · Power BI · Delta Lake · Python What sets me apart is ownership\. I take ambiguous data problems, architect clean solutions, and measure the outcome\. I've worked across data ingestion, transformation, quality validation, and BI reporting — giving me full\-pipeline visibility that most engineers in my space don't have\. I'm actively exploring Data Engineering / Analytics Engineering roles where I can contribute to data platform architecture and drive real business decisions through reliable data infrastructure\. 📩 Open to conversations — DM me or reach out at abhishekchavan1798@gmail\.com

## Location

Mumbai Metropolitan Region

## AI stack

gemini

langchain

ollama

openai

## Work experience

Data Engineer at Cognizant, Nov 2022 \- Present · 3 yrs 8 mos, Pune District, \- Architected end\-to\-end ETL pipelines on Azure Databricks \+ Apache Spark, processing 1M\+ records daily with 99\.9% SLA adherence \- Slashed reporting latency by 30% by re\-engineering data transformation logic, directly improving time\-to\-insight for downstream analytics teams \- Engineered a custom data ingestion framework that reduced dependency on Azure Data Factory, cutting infrastructure costs by $800/month \(\~$9,600/year\) \- Automated batch processing workflows end\-to\-end, improving operational efficiency by 40% and cutting execution time by 80% \- Drove data quality across pipelines through rigorous SQL and PySpark\-based cleansing, transformation, and validation — reducing downstream reporting errors \- Optimized Spark jobs and SQL queries for compute efficiency, reducing cluster runtime and cutting cloud resource costs \- Delivered 5\+ Power BI dashboards for business intelligence teams, enabling self\-serve analytics for non\-technical stakeholders \- Maintained SLA\-based data refresh processes across production pipelines, ensuring zero downtime for critical business reporting

## Education

Master of Computer Applications \- MCA, Information Technology, MIT Arts, Commerce &amp; Science College \( MITACSC \)

Bachelor of Science \- BS, University of Mumbai

[View the original profile](https://tal.club/meet/abhishek-61)

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