---
title: "Nayan Ghule - Senior Software Engineer - Data Engineering in Pune Division | Tal"
description: "Meet Nayan Ghule, Data Engineer || Ex-Infocian || Azure Data Engineer,Databricks ,Microsoft Fabric ,PySpark,ADF | I Design Scalable ETL Pipelines| 3x Microsoft Certified | Open to Sponsored Roles in EU / UK / UAE /canada/USA based in Pune Division. AI stack includes claude code, langchain, and lova..."
image: "https://tal.club/meet/nayan-ghule/share-image"
---

# Nayan Ghule on Tal

## Headline

Data Engineer \|\| Ex\-Infocian \|\| Azure Data Engineer,Databricks ,Microsoft Fabric ,PySpark,ADF \| I Design Scalable ETL Pipelines\| 3x Microsoft Certified \| Open to Sponsored Roles in EU / UK / UAE /canada/USA

## About

I’ve built data pipelines\. I’ve fixed them at 3 AM\. I’ve optimised them so they don’t break again\. I’m a Data Engineer with 4 years of hands\-on experience building and running large\-scale data platforms on Azure — currently at ZS Associates, one of the top global analytics and consulting firms serving pharma and life sciences clients worldwide\. What I build: 10\+ production\-grade pipelines processing 500K\+ records daily across Medallion architecture \(Bronze → Silver → Gold\) using PySpark, Databricks, Delta Lake, ADF, and Synapse\. I’ve improved ingestion and transformation performance by up to 60%, cut compute costs by 40%, and delivered end\-to\-end POCs across the full Azure data stack including Power BI\. Spark tuning — partitions, caching, AQE — is bread and butter for me\. What I’ve survived: Real production failures\. Debugging distributed Spark jobs at scale, root\-cause analysis with Splunk, SCD Type 2 MERGE logic across 4\-table dimension chains, data quality issues mid\-pipeline\. 99%\+ uptime wasn’t a metric we reported — it was one we maintained\. That experience shapes how I design systems today: observability\-first, failure\-tolerant, built to last\. Prior to ZS, I was at Infosys on the Capital Group account — a US\-based global asset management firm managing \~$2\.5T in AUM\. Financial data pipelines, tight SLAs, no room for error\. Certifications: Microsoft Fabric Data Engineer Associate \(DP\-700\) · Azure Data Engineer Associate \(DP\-203\) · Databricks Data Engineer \(in progress\) Stack: Python · PySpark · SQL · Databricks · Delta Lake · Azure Data Factory · Synapse Analytics · Microsoft Fabric · Airflow · Power BI 🌍 Open to Senior Data Engineer roles internationally — UK, EU \(Netherlands, Germany, Ireland\), UAE, and USA\. Comfortable with visa sponsorship processes and available to relocate\. If you’re hiring engineers who understand both how systems are built and how they fail — let’s talk\. I move fast\.

## Location

Pune Division

## AI stack

claude code

langchain

lovable

n8n

notebooklm

openai

## Work experience

Senior Software Engineer \- Data Engineering at Inteliment Technologies, Nov 2025 \- Present · 9 mos, Pune District, Maharashtra, India, ZS Associates \(via Intelliment\) — Data Engineer The work here sits at the intersection of traditional data engineering and GenAI automation — building on top of a 5M\+ records/month ERP data platform while prototyping agentic workflows that let finance stakeholders query data in plain English\. • Prototyped LangChain \+ LangGraph agentic workflows on Databricks enabling natural language querying over 5M\+ monthly finance records — replacing manual reporting cycles for business stakeholders • Built LLM\-powered data assistants for automated insight generation and pipeline documentation, cutting analyst turnaround on ad\-hoc requests by \~35% • Engineered end\-to\-end ERP data pipelines powering 400\+ finance dashboards with automated validation and reconciliation checks, reducing manual verification effort by \~30% • Debugged schema mismatches, ingestion failures, and transformation\-layer defects across pipelines serving 50\+ business users • Implemented structured monitoring and alerting frameworks, cutting incident resolution time by \~25% Stack: Databricks · LangChain · LangGraph · Python · SQL · Azure Data Factory · Delta Lake

Technology Analyst at Infosys, Oct 2025 \- Nov 2025 · 2 mos, Pune District, Maharashtra, India, Senior\-most IC role at Infosys\. Owned the most complex data engineering work on the Capital Group account — a US\-based global asset management firm managing \~$2\.5T in AUM\. Designed, optimised, and delivered production systems at scale\. • Architected high\-throughput ingestion pipelines pulling heterogeneous financial data from multiple sources into Azure Data Lake using Databricks and Delta Lake — improving ingestion speed and reliability by \~60% • Led migration of legacy data architecture to Microsoft Fabric, achieving a 40% performance boost and improving data accessibility for downstream analytics consumers • Optimised Spark jobs and Delta table partitioning strategies, reducing compute costs and query runtimes by \~60%; applied Spark SQL indexing to accelerate BI query performance • Orchestrated complex multi\-dependency workflows via ADF and Apache Airflow with modular Python/SQL pipelines, robust error handling, and task backtracking — maintaining 99%\+ pipeline uptime • Built end\-to\-end ETL pipelines in Microsoft Fabric using Dataflow Gen2 \(SharePoint → Lakehouse\), supporting analytics at enterprise scale • Evaluated Azure Cosmos DB \(MongoDB API\) for real\-time ingestion migration from MongoDB Atlas — led performance benchmarking and indexing strategy • Delivered interactive Power BI dashboards for investment strategy teams; monitored pipeline health via Splunk with proactive root\-cause analysis on data anomalies Stack: Databricks · Delta Lake · Azure Data Factory · Apache Airflow · Microsoft Fabric · Python · PySpark · Spark SQL · Power BI · Splunk · MongoDB · ADLS Gen2

Senior System Engineer at Infosys, Oct 2024 \- Oct 2025 · 1 yr 1 mo, Pune District, Maharashtra, India, Stepped up from data ops into full ownership of pipeline development\. Took on progressively complex transformation and orchestration work as a hands\-on data engineer\. • Built 10\+ production\-grade pipelines processing 500K\+ records daily using Databricks and ADLS Gen2 • Designed MongoDB and SQL Server schemas that improved query performance by 30% • Led ADF data integration refactoring that reduced pipeline redundancy by 35% and improved transformation speed by 25% • Owned Spark performance tuning — partition sizing, caching strategies, broadcast joins — to optimise job runtimes across production workloads • Began taking ownership of end\-to\-end pipeline delivery: design, build, test, and handover with documentation Stack: Databricks · PySpark · Azure Data Factory · Delta Lake · SQL Server · MongoDB · ADLS Gen2

System Engineer at Infosys, Oct 2022 \- Oct 2024 · 2 yrs 1 mo, Pune District, Maharashtra, India, Transitioned from training into the Capital Group data platform team\. Started in a DataOps capacity — monitoring, incident response, pipeline health — and progressively took on development work as I built familiarity with the production environment\. • Monitored pipeline health and performed root\-cause analysis on ingestion and transformation failures across Azure Data Lake pipelines • Supported Databricks and ADF pipeline runs — triage, diagnosis, and escalation of data quality issues • Wrote SQL and PySpark scripts for data validation, reconciliation, and ad\-hoc data extraction • Gained hands\-on exposure to Medallion architecture, Spark internals, and Delta Lake operations in a live financial data environment • Gradually shifted toward development tasks — fixes, enhancements, and small\-scale pipeline builds — under senior engineer mentorship Stack: PySpark · SQL · Azure Data Factory · Databricks · Delta Lake · Splunk

Intern at Verzeo, May 2021 \- Aug 2021 · 4 mos, Gained hands\-on experience in Python, SQL, and machine learning\. Developed multiple ML models \(classification/regression\) on real datasets, applying data preprocessing, feature engineering, and evaluation best practices\.

## Education

Bachelor of Engineering, Information Technology, Savitribai Phule Pune University

## Public links

- github: https://github\.com/Naynx7

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

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