---
title: "Aayush Pardeshi - Data Engineer in Pune City | Tal"
description: "Meet Aayush Pardeshi, Data Engineer | PySpark · Azure Databricks · Airflow · Spark SQL · Hive · AWS EMR | ETL Pipeline | Pune based in Pune City."
image: "https://tal.club/meet/aayush-22/share-image"
---

# Aayush Pardeshi on Tal

## Headline

Data Engineer \| PySpark · Azure Databricks · Airflow · Spark SQL · Hive · AWS EMR \| ETL Pipeline \| Pune

## About

I build the pipelines that make data usable at scale\. Around 2 years of hands\-on experience as a Data Engineer, I specialize in designing and optimizing high\-performance ETL pipelines using PySpark, Apache Spark, and Azure Databricks — processing millions of records daily from sources like Azure Blob Storage, AWS S3, and Snowflake\. At Vodafone Idea \(Vi\), I engineered PySpark\-based workflows on AWS EMR, automated job orchestration via AWS Step Functions, and consistently resolved production bottlenecks that kept data SLAs intact\. At DGLiger, I've leveled up into Databricks \+ Airflow territory — building DAG\-orchestrated batch pipelines and integrating data quality checks into every layer\. What I bring to the table: → End\-to\-end ETL pipeline design \(batch \+ incremental loads\) → Spark performance tuning: partitioning, caching, predicate pushdown → Workflow orchestration with Apache Airflow → File format expertise: Parquet, Avro, ORC, JSON, CSV → Cloud\-native data engineering on AWS \(EMR, S3\) & Azure \(Databricks, Blob Storage\) → Data warehousing with Snowflake and Hive I'm actively seeking Data Engineer / Big Data Engineer roles in Pune where I can contribute to building robust, scalable data infrastructure\.

## Location

Pune City

## Work experience

Data Engineer at DGLiger Consulting, Feb 2026 \- Present · 5 mos, Pune Division, • Built and maintained scalable ETL pipelines using PySpark on Azure Databricks, processing large\-scale structured and semi\-structured data from Azure Blob Storage and Snowflake with high reliability\. • Designed and orchestrated end\-to\-end Airflow DAGs, reducing manual intervention in batch pipeline scheduling by automating dependency management and alerting on failures\. • Integrated Databricks notebooks into Airflow workflows, enabling fully automated batch data processing cycles and improving pipeline observability\. • Implemented Spark performance tuning techniques \(partitioning, caching, broadcast joins, predicate pushdown\), resulting in measurable reduction in job execution time\. • Enforced data quality through validation logic at ingestion and transformation layers, reducing downstream data errors for business reporting teams\. • Managed source code versioning, deployment, and collaboration using Atlassian Bitbucket\.

Big Data Engineer at Vodafone Idea Limited, Sep 2024 \- Oct 2025 · 1 yr 2 mos, Pune, Maharashtra, India, • Designed and implemented PySpark\-based ETL pipelines on AWS EMR for large\-scale data processing\. • Used Spark SQL and DataFrames for data transformation, aggregation, and analytics\. • Designed and implemented Spark jobs using Python\. • Implemented Spark SQL queries for data querying and aggregation\. • Developed custom Spark functions for complex data transformations\. • Worked with Spark's data serialization formats \(Avro, Parquet, JSON, etc\.\)\. • Debugged and optimized Spark code for performance bottlenecks\. • Designed and implemented ETL processes using Spark\. • Designed efficient PySpark workflows on AWS EMR for processing AWS S3 data\. • Automated Spark job executions on AWS EMR clusters using AWS Step Functions\.

Intern at Vodafone Idea Limited, Jan 2024 \- Apr 2024 · 4 mos, Pune, Maharashtra, India

## Education

Bachelor of Engineering \- BE, Electronics and Telecommunication, Dr\. D\. Y\. Patil Institute of Technology, Pimpri, Pune

Bachelor of Engineering \- BE, Electrical, Electronics and Communications Engineering, Savitribai Phule Pune University \(SPPU\)

[View the original profile](https://tal.club/meet/aayush-22)

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