Shreyansh
Dubey
I take a business problem — not a ticket — and build the data platform, governed BI and engineering behind it.
- 5.5+ years of client delivery
- 17 engineers led across two concurrent engagements
- ~200 enterprise users on a governed Fabric platform
- US · UK client delivery, working remotely
Selected clients
The practice
Most analytics work fails at the translation, not the tooling.
Five and a half years of client delivery across banking, wealth and asset management, travel, healthcare and manufacturing — usually as the person standing between the business question and the system that had to answer it. The engagements below start with what was wrong, not with what was built.
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01
Understand the problem first
Requirements gathering with finance, operations and product leadership — then KPI definitions everyone has actually agreed to, before anything is modelled.
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02
Design the system, not the report
Target-state architecture, lakehouse and warehouse design, and governed semantic models that hold their definitions so the estate stays trustworthy as it grows.
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03
Build what people decide with
Executive and operational dashboards, funnel, retention and churn measurement, and financial analytics — built around the decision rather than around the shape of the data.
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04
Automate what shouldn't be manual
Manual consolidation, paper workflows and third-party dependencies rebuilt as systems that run themselves on tooling the organisation already owns.
Selected work
Four problems, and what changed
Consulting
Where I'm brought in
Working together
Four ways to engage
Rates depend on scope, duration and region, and are agreed in conversation rather than published here.
Tell me what's not working.
A short discovery conversation is usually enough to tell whether I'm the right person for the problem — and if I'm not, to point you at what is.