---
title: "Jayendra singh Rajpoot - Business Analyst in Pune/Pimpri-Chinchwad Area | Tal"
description: "Meet Jayendra singh Rajpoot, Software Engineer | AWS Certified | Spark · PySpark · AWS Glue · Redshift| Capital Markets & BFSI | 5 Yrs | Open to Forward Deployed Engineer /Senior DE / Cloud Data Engineer Roles | Immediate Joining Availability based in Pune/Pimpri-Chinchwad Area. AI stack includes c..."
image: "https://tal.club/meet/jayendra-singh-rajpoot/share-image"
---

# Jayendra singh Rajpoot on Tal

## Headline

Software Engineer \| AWS Certified \| Spark · PySpark · AWS Glue · Redshift\| Capital Markets & BFSI \| 5 Yrs \| Open to Forward Deployed Engineer /Senior DE / Cloud Data Engineer Roles \| Immediate Joining Availability

## About

💸 Cut 75% of AWS compute costs\. Reduced pipeline runtimes by 40%\. Delivered 6 critical data feeds a month ahead of schedule — and triggered a 12\-person team expansion\. That's the production record I've built over 5 years as a Software Engineer, engineering cloud\-native ETL/ELT systems for Capital Markets and BFSI workloads on AWS\. 🛠️ MY CORE STACK: • PySpark on AWS Glue & Apache Spark • Amazon S3 \(Lakehouse Foundation\) & Amazon Redshift • AWS Step Functions, Lambda, DynamoDB, & CloudWatch • DevOps: Linux, Docker, Ansible, Jenkins, Git I architect Medallion Lakehouse systems \(Bronze\-Silver\-Gold\), design schema contracts, and own the full pipeline lifecycle — from mainframe source migration through to downstream feed delivery\. I successfully migrated 50\+ mainframe batch workloads to a distributed AWS architecture, processing 40–60 GB/day with a strict 0% SLA breach rate across all delivery tracks\. 📈 ENGINEERING HIGHLIGHTS: • Optimized critical Glue jobs via partition pruning and broadcast joins — cutting worker footprint from 20 to 5 DPUs \(75% cost drop\)\. • Re\-engineered a memory\-bound validation script into a distributed PySpark job, catching 4\+ critical data\-skew defects monthly before production\. • Built fault\-tolerant workflows using Lambda DLQs, S3 Lifecycle policies, and DynamoDB state management to sustain 100% data availability\. 👥 LEADERSHIP & ALIGNMENT: As a Senior Data Engineer, I translate ambiguous business requirements into concrete data contracts for a 6\-member client team, de\-risking delivery timelines\. I've mentored 4 engineers on cloud architecture and Spark optimization — increasing team delivery capacity 3x and enabling the business to onboard two additional project workstreams\. 🎯 WHAT I’M LOOKING FOR: Targeting Senior Data Engineer, AWS Data Engineer, Cloud Data Engineer, and Big Data Engineer roles at product companies, MNCs, and engineering\-focused organizations\. 🚀 AVAILABILITY: Currently serving notice period and actively interviewing\. Open to opportunities across Bengaluru, Hyderabad, Pune, Noida, Gurugram, Indore, and Remote\. 📬 Let's Connect: Looking to scale your data infrastructure or migrate legacy architectures? Drop a line here or reach out directly at jayendrarajpoot200@gmail\.com

## Location

Pune/Pimpri\-Chinchwad Area

## AI stack

claude code

cursor

gemini

openai

claudecode

## Work experience

Business Analyst at FCG Bhopal, Dec 2025 \- Jun 2026 · 7 mos, Bhopal, Madhya Pradesh, India, \-Spearheaded the implementation of AI\-driven data extraction workflows, configuring advanced document classification models for efficient processing\. \- Defined precise field\-mapping rules to convert unstructured legal and title documents into structured, queryable datasets, significantly automating data ingestion processes\. \- Served as the technical liaison for Flairdocs, a land acquisition and Right\-of\-Way data platform utilized by U\.S\. state Departments of Transportation \(DOTs\)\. \- Translated complex business logic into detailed data mapping specifications, schema configurations, and technical pipeline requirements, thoroughly documented in Confluence\. \- Directed end\-to\-end testing for data\-centric feature releases, meticulously tracking data ingestion and integration defects using JIRA\. \- Maintained comprehensive data lineage and requirements traceability to ensure data integrity throughout the development cycle\. \- Authored clear and detailed technical implementation guides to support client data teams in system integration and maintenance\. \- Validated API\-driven data pipelines and RESTful integrations using Postman and Swagger across core microservices, ensuring accurate payload delivery\. \-Ensured secure data ingestion and seamless data exchange between Parcel Management, Payment Creation, and Dispostion modules, enhancing system interoperability\.

Software Engineering Analyst at Accenture, Apr 2024 \- Nov 2025 · 1 yr 8 mos, Pune District, Maharashtra, India, The platform existed\. What it lacked was someone who owned it — who could see where it would fail under load and fix the architecture before that happened\. That's the gap I stepped into as Senior Data Engineer\. I own the full data platform for a Capital Markets reporting stack on AWS: pipeline design, data contracts, SLA accountability, and the production incidents that come with all of it\. ▸ Redesigned the validation layer — converted a memory\-bound Python script into a distributed PySpark job via Step Functions, catching 4\+ critical data skew defects monthly before they reach production\. ▸ Engineered fault\-tolerant workflows using Lambda DLQs, DynamoDB state management, and S3 Lifecycle policies — sustained 0% SLA breaches across all Capital Markets delivery tracks\. ▸ Translated ambiguous business requirements into formal data contracts for a 6\-member client team — eliminated rework cycles and secured delivery alignment across all milestones\. ▸ Mentored 4 engineers on Spark optimization and cloud architecture — increased team delivery capacity 3x, enabling the business to onboard 2 additional project workstreams\. I didn't just keep the platform running — I made the team around it self\-sufficient\.

Software Engineer at Accenture, Jan 2022 \- Apr 2024 · 2 yrs 4 mos, India, The data infrastructure was mainframe\-first — scheduled batch jobs, no cloud layer, no observability, no lakehouse\. My job was to change all of that\. Designed and led the migration of 50\+ mainframe workloads to a Medallion Lakehouse on AWS, built on S3, Glue, and PySpark — taking the platform from legacy batch processing to a distributed architecture handling 60 GB of daily Capital Markets data\. ▸ Reduced daily pipeline runtime by 40% through partition pruning, broadcast join optimization, and Spark tuning — zero SLA breaches across all production delivery tracks\. ▸ Cut AWS Glue DPU consumption by 75% \(20 → 5 DPUs\) — eliminated runaway compute cost while maintaining full throughput and data quality\. ▸ Built a modular PySpark ETL framework executing 120\+ parallel transformations — standardized incremental load patterns and cut new data feed onboarding time by 60%\. ▸ Developed a Python\-native data quality engine within Step Functions enforcing schema contracts across 6 downstream feeds — no feed shipped to reporting without passing that gate\. Delivered 6 of 11 critical data feeds one month ahead of schedule — directly triggering a 12\-person team expansion and earning promotion to Senior Data Engineer\.

Software Engineer at Cheers Infinity, Dec 2020 \- Jan 2022 · 1 yr 2 mos, Bhopal, Madhya Pradesh, India, \- Engineered robust backend microservices and RESTful APIs using Python \(FastAPI, Django\), Node\.js, and Java to support responsive web platforms and dynamic mobile applications\. \- Ensured seamless integration between front\-end interfaces and PostgreSQL databases, optimizing performance for hightraffic client deployments\. \- Spearheaded the integration of Generative AI capabilities into enterprise applications, designing and deploying RetrievalAugmented Generation \(RAG\) architectures with LLM APIs \(OpenAI, Anthropic\)\. \- Automated high\-quality content generation, streamlined creative workflows, and developed intelligent chatbots to enhance client platform interactions\. \- Engineered reliable ETL pipelines leveraging Python and SQL to extract, process, and ingest complex datasets into centralized data repositories\. \- Collaborated closely with Data Science teams to enable predictive analytics and machine learning model deployment\. \- Developed automated data\-harvesting scripts and API integrations to consolidate SEO, PPC, and social media metrics for digital marketing automation\. \- Built backend architectures for custom analytics dashboards delivering prescriptive and diagnostic insights, enabling marketing teams to optimize campaigns and maximize ROI\. \- Containerized and deployed web and data applications using cloud platforms, enhancing scalability and reliability through DevOps best practices\.

## Education

Bachelor of Technology, Electrical, Electronics and Communications Engineering, Oriental Institute of Science & Technology

High School Diploma, Kendriya Vidyalaya \- No\. 2

[View the original profile](https://tal.club/meet/jayendra-singh-rajpoot)

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