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Nishkarsh Jain

Data & AI Platform Advisor

I help enterprises choose their data and AI platform.

Explore my work
Nishkarsh Jain
ExpertiseSolution ArchitectureData Cloud & AI PlatformsTechnical Sales and GTMDeal Bid & Proposal ManagementValue Engineering
AvailabilityOpen for Enterprise AdvisoryBengaluru, India11:30–18:30 UTCSenior Solutions Engineer, e6data
SectorsTechnology & SoftwareFinancial Services & InsuranceRetail & Consumer GoodsHealthcare & Life SciencesManufacturingLogistics
RegionsUS · UKFortune 500 enterprises

Years on the vendor’s side of these evaluations. Now that experience works for the buyer: an informed choice, and real return on what they pick.

What I work with

Experience

  • e6data
  • Capgemini
  • kipi.ai
  • Apisero
  • WNS
  • Accenture
  • Aivamastu
  • Data Cult
  • duochat

Technology

  • Streamlit
  • Python
  • Docker
  • MySQL
  • PostgreSQL
  • Apache Spark
  • Apache Kafka
  • Apache Iceberg
  • Matillion
  • Fivetran
  • dbt
  • Microsoft Azure
  • AWS
  • Databricks
  • Snowflake

Who this is for

Two very different buyers, one decision

The same decision under opposite pressures. Here is what I do for each.

Enterprise evaluation

You have a shortlist, a proof of concept to run and a committee to convince.

  • Set the success criteria with your sponsor before any vendor touches your data, so the proof answers your question and not theirs.
  • Pressure-test each shortlisted architecture, price and benchmark against your real workloads and concurrency.
  • Build the business case and total cost of ownership your CFO and risk committee will sign.

What you leave with: A recommendation your committee can defend, usually two to three weeks after discovery starts.

Start with the shortlist

Founding team

You are picking a stack for the next eighteen months, not the next ten years.

  • Choose the warehouse, lakehouse or query engine for your current scale and the one after it, with the exit path written down.
  • Get a working prototype on your real data in two to four weeks, kept deliberately narrow.
  • Decide what to build, what to buy and what to defer, with the cost of each.

What you leave with: An architecture your first data hire can build against, and a prototype your investors can see.

Tell me about the stack

Selected impact

Four of eight engagements, described as far as confidentiality allows

Client names stay private. The measured result does not.
All case studies

Track record

  • 7+

    Years across Data, AI & Cloud Solutioning and GTM

  • 200+

    Companies taken through a data or AI platform decision

  • 2 → 12

    Solutions Engineering team scaled

  • $31M+

    Won business across 320+ customer wins

What I do

Where I come in, from strategy to the deal

See each one in full
Every engagement starts from a commercial question, not a technology preference.

Beyond the work

Beyond the architecture diagrams, there is always another road.

My wife and I travel as a couple and document it properly — cinematic short films, honest write-ups of the stays, and itineraries detailed enough to actually follow.

Explore my journeys@nishkarrsh

Start a conversation

Build the next decision, partnership, or hire.

Consulting project

A platform evaluation, a build-or-buy call, or a GenAI pilot that has to survive a risk review. For enterprise committees and founding teams alike.

Describe the decision

Fractional SE leadership or a senior role

A vendor whose technical evaluations need running properly, a senior role, or a panel or advisory board.

Get in touch

I read every message myself and reply within two working days. What you share about a live evaluation stays between us.

nishkarsh@nishkarshjain.comBook an introductory call(opens in a new tab)Download résumé (PDF)