Nilansh Arora

Product Manager

Pune, Maharashtra, India9 yrs 2 mos experience

AI EnabledHighly Stable

Key Highlights

Expert in building scalable AI-driven data systems.
Led successful migration from Redshift to Databricks.
Developed innovative AI solutions for EdTech.

Stackforce AI infers this person is a SaaS-focused Data Engineer with strong AI and data management expertise.

Contact

Skills

Core Skills

Data ManagementApache SparkMachine LearningData EngineeringWeb Development

Other Skills

Amazon RedshiftAmazon Web Services (AWS)AnalyticsAngular JSApache KafkaApache Spark StreamingCC++Cascading Style Sheets (CSS)Chatbot DevelopmentDatabasesDatabricksFront-end CodingGitHTML

About

🧠💻 Living at the edge of AI and data — and loving it. I’ve been diving deep into the latest in AI tech, building smart, scalable systems that actually work in the real world. From LLMs to data pipelines, I’ve been hands-on with it all. ⚙️ Recently, I’ve been leading the charge on migrating from Redshift to Databricks, squeezing out performance while keeping costs in check (yes, cost optimization is my guilty pleasure). 🔧 I play around with tools like Databricks, AWS Glue, S3, MCP, and whatever shiny new thing makes sense for the job. My days are a mix of building, optimizing, and figuring out how to make data (and AI) work harder and smarter. Big fan of systems that scale, code that’s clean, and coffee that’s strong. Let’s build cool stuff.

Experience

9 yrs 2 mos

Total Experience

3 yrs 5 mos

Average Tenure

2 yrs 3 mos

Current Experience

Angel one

Lead Data Engineer

Jul 2024 – Present · 1 yr 10 mos · Pune, Maharashtra, India · Hybrid

At Angel One, I’m leading the charge on building a next-gen Lakehouse architecture on Databricks, shaping how data flows, transforms, and empowers decision-making across the company.
I’m focused on leveraging AI tech not just for the cool factor — but to solve real business problems and bring intelligence into every layer of our data ecosystem.
✨ Some things I’m driving:
Architecting and implementing the Lakehouse platform using Databricks & the modern data stack
Spearheading the complete data quality framework — ensuring clean, reliable data for every stakeholder
Leading the migration from Redshift to Databricks, with performance gains and cost savings at the core
Hands-on with S3, AWS Glue, MCP, and constantly experimenting with the latest in AI and data engineering
I believe in building systems that scale, teams that collaborate, and data that tells a story (a reliable one). Always excited about what’s next in the world of AI + data.

Data ManagementApache Spark StreamingTeam ManagementDatabasesAnalyticsApache Spark

Self-employed

AI and Latest Tech Consultant

Feb 2024 – Present · 2 yrs 3 mos · Pune, Maharashtra, India

Worked across multiple impactful AI-first projects, blending NLP, data engineering, and smart automation to solve real-world problems:
🔹 Helping KhareClasses build hard core tech and AI product, growing the product experience of students across India learning Maths. Help in building multiple agents across the platform under Proprietary ICEAM Framework which can power the overall edtech system and create the future of AI tutor. Agents involving Parent corner support, Monitoring Agents, Content Agents, etc
🔹 Automated SQL Generation Engine – Built a powerful engine (1.5 years back) that turned RAG (retrieval augmented generation) into dynamic SQL queries, enabling analytics at scale with minimal human input.
🔹 Math Doubt Solver + Human Interpreter – Created an AI system that could interpret and solve student math doubts in a human-like, interactive way – tailored especially for younger learners.
🔹 RAG-based FAQ Chatbots – Developed FAQ bots for product support using RAG pipelines, making customer queries feel more natural, accurate, and context-aware.
🔹 Sales & Marketing Intelligence System – Designed a system to scrape, track, and generate insights on what parallel companies are doing in the market — helping sales teams stay sharp and informed.
Each project pushed the limits of what AI + engineering could achieve, and helped turn raw data into real value.