---
title: "Atharva Jibhakate - Data Engineer in Pune Division | Tal"
description: "Meet Atharva Jibhakate, Senior Data Engineer | Databricks | PySpark | Apache Spark | Airflow | Snowflake | AWS | ETL/ELT | Data Lakehouse | Data Warehousing | Data Platforms based in Pune Division."
image: "https://tal.club/meet/atharva-17/share-image"
---

# Atharva Jibhakate on Tal

## Headline

Senior Data Engineer \| Databricks \| PySpark \| Apache Spark \| Airflow \| Snowflake \| AWS \| ETL/ELT \| Data Lakehouse \| Data Warehousing \| Data Platforms

## About

Senior Data Engineer with 4\+ years of experience designing and building scalable cloud\-native data platforms and ETL/ELT pipelines\. Currently working in the GrowthOS product team at Publicis Groupe, where I develop large\-scale data solutions using Databricks, PySpark, Apache Spark, Airflow, Snowflake, Delta Lake, and AWS\. My work focuses on data platform modernization, pipeline orchestration, data warehousing, metadata\-driven engineering, and performance optimization\. Previously at UST, I worked on enterprise healthcare insurance data platforms for Blue Cross Blue Shield Association, developing high\-volume data pipelines on AWS using Glue, Lambda, Spark, Iceberg, and Redshift\. Key expertise: • Databricks & Lakehouse Architecture • PySpark & Apache Spark • Airflow Orchestration • Snowflake & Data Warehousing • ETL / ELT Development • AWS Data Engineering • Data Modeling & Performance Optimization Databricks Certified Data Engineer Associate\. Open to opportunities involving modern data platforms, large\-scale analytics engineering, and cloud\-native data architecture\.

## Location

Pune Division

## Work experience

Data Engineer at Publicis Groupe, Feb 2025 \- Present · 1 yr 6 mos, Pune District, Maharashtra, India, Product: GrowthOS Campaign Manager Platform Working as a Senior Data Engineer in the GrowthOS product team, responsible for designing and developing large\-scale cloud\-native data platforms and analytics solutions for global marketing and advertising use cases\. • Design and develop scalable ETL/ELT pipelines using Databricks, PySpark, Apache Spark, Airflow, Delta Lake, Snowflake, and AWS\. • Build and maintain data products following Lakehouse and Medallion Architecture principles \(Bronze, Silver, Gold layers\) to support analytics and business intelligence workloads\. • Develop metadata\-driven frameworks and reusable pipeline components to improve scalability, maintainability, and onboarding of new client data sources\. • Lead migration and modernization initiatives from legacy Redshift\-based architectures to Databricks Lakehouse, improving performance, reliability, and operational efficiency\. • Orchestrate end\-to\-end workflows using Apache Airflow and Databricks Workflows, ensuring reliable execution and monitoring of production data pipelines\. • Implement data quality validation, performance optimization, and operational monitoring strategies to support enterprise\-scale datasets\. • Deliver outbound data integrations to downstream platforms including Snowflake and Redis, enabling faster data access and analytical consumption\. • Collaborate with global cross\-functional teams across Product, Engineering, Analytics, and Data Science to deliver scalable data solutions\. • Contribute to AI\-powered metadata enrichment initiatives using Claude Sonnet, enhancing dataset discoverability, documentation quality, and governance capabilities\.

Developer II \- Enterprise Solutions at UST, Jun 2024 \- Feb 2025 · 9 mos, Pune District, Maharashtra, India, Client: Blue Cross & Blue Shield Association • Designed and developed scalable ETL pipelines using AWS Glue, PySpark, Lambda, EC2, CodeBuild, and Spark, integrating data from S3, PostgreSQL, and Elasticsearch\. • Built serverless data processing frameworks using AWS Lambda, Glue Workflows, and SNS, enabling automated monitoring, fault tolerance, and real\-time alerting\. • Optimized large\-scale PySpark workloads using Broadcast Joins, Repartitioning, Salting, Caching, and skew handling techniques, reducing ETL execution time from 60 minutes to 25 minutes and lowering operational costs by 40%\. • Developed a high\-performance Change Data Capture \(CDC\) framework using Apache Iceberg, Spark SQL, and AWS Glue, improving incremental data processing efficiency and resource utilization by 30%\. • Engineered and maintained data pipelines processing 10\+ TB of data daily, delivering curated datasets to Elasticsearch for enterprise analytics and search workloads\. • Led performance tuning initiatives using AWS CloudWatch and AWS X\-Ray, identifying bottlenecks and improving pipeline execution performance by 50%\. • Automated operational reporting and monitoring workflows using AWS Lambda and SNS, reducing manual effort and improving production visibility\. • Implemented security and governance best practices using AWS KMS, IAM, encryption standards, and access controls to ensure compliance with enterprise data policies\. • Collaborated with DevOps, QA, and business stakeholders during release cycles, supporting CI/CD deployments through AWS CodePipeline and ensuring production stability\.

Cloud Infrastructure Associate II at UST, Jan 2024 \- May 2024 · 5 mos, Pune District, Maharashtra, India

Big Data & Cloud Associate at UST, Jan 2023 \- Dec 2023 · 1 yr, Pune District, Maharashtra, India

Google DSC Team Member at Google Developer Student Clubs MIT\-WPU, Dec 2020 \- May 2022 · 1 yr 6 mos, Pune, Maharashtra

Full Stack Developer Intern at Applus\+ IDIADA, Mar 2021 \- Jun 2021 · 4 mos, Pune Division, Maharashtra, India, ● Develop, review, and optimize intra\-company portal for file I/O management for CAE department to ease the process for mechanical engineers\. ● Ensure maximum productivity by working on Utility Portal for managing various aspects of project management and to keep all project\-related utilities at one place\. ● Established end\-to\-end data pipeline and supplied data to frontend on interactive dashboards for live dynamic data visualization and added functionality for live data comparison of different modules\. ● Deployed the live application for the department employees to use and received A grade feedback from the HOD\.

ML & SDE Intern at HELO HEALTH, Nov 2020 \- Jan 2021 · 3 mos, Thane, Maharashtra, India, ● Developed scalable Employee Identification & Diagnosis system for a back to office solution to provide real time insights of employees’ health\-related data and also integrated facial attendance system\. ● Devised and created a new algorithm which alerted administrator if health data patterns of an employee reach the danger level\. ● Partnered with cross\-functional UI development team for developing backed \(Django & MongoDB\) in a portal for administrator to manage all data in one place\. ● This system was deployed across the metro cities of Mumbai & Delhi in various offices\.

## Education

Bachelor of Technology \- BTech, Computer Science Engineering, MIT World Peace University

[View the original profile](https://tal.club/meet/atharva-17)

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