Services
Video meeting . 60 mins
Data Engineering Mock Interview
Practise technical reasoning and get actionable feedback.
Video meeting . 30 mins
Data Engineering Career Mentorship
A focused roadmap for your next data engineering role.
Video meeting . 30 mins
GenAI for Data Engineers
Understand RAG and agents through a data-platform use case.
Video meeting . 30 mins
Spark / SQL Troubleshooting
Diagnose one bottleneck. Build a practical debugging plan.
Video meeting . 30 mins
Senior / Lead System Design Mock
Practise architecture trade-offs for senior and lead roles.
Video meeting . 30 mins
Resume + Interview Strategy Review
Make your projects and engineering impact easier to explain.
Video meeting . 30 mins
AI Data Platform Architecture
Review the path from a business question to a useful answer.
About me
Build stronger foundations. Prepare for your next role. Understand how modern data and AI systems work in practice.
I'm Prakhar, a Senior Data Engineer at Airtel Digital with 8+ years of industry experience. I help data engineers with interviews, system design, career decisions and the move into AI-powered data platforms.
MY ENGINEERING JOURNEY
Data pipelines → distributed systems → cloud data platforms → semantic search & RAG → AI agents & analytics.
I started with SQL, Python, Spark and large-scale data processing. Over time, my work evolved into data platform engineering. Today, I work on systems that understand business questions, discover relevant enterprise data, generate and validate SQL, execute queries and return useful answers.
That journey connects traditional data engineering with metadata intelligence, semantic retrieval, agent workflows and reliable query execution. My broader experience spans ecosystems involving Airtel Digital, GlobalLogic, Expedia Group / Hotwire, Publicis Sapient and Cognizant.
HOW I CAN HELP
• Prepare for Data Engineer and Senior / Lead interviews.
• Practise system design and explain engineering trade-offs.
• Strengthen your resume, project stories and career roadmap.
• Learn GenAI, RAG and agents from a data engineer's perspective.
• Review an AI data platform design or troubleshoot a focused Spark / SQL problem.
My approach is practical: understand why a system exists, how its parts fit together and what happens when it fails. Bring a specific goal or challenge, and we'll work through it together.
Explore the sessions below and choose the one that matches your next step. For technical reviews, bring anonymised examples without credentials or confidential employer data.