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Est. 2016·Day 0000·
Available for new engagements · Q2 2026
Cairo ·GMT+2·

Mahmoud Amr
Architecture · Data · Cloud & AI · Top-Rated since 2016


§ AI & Data Platform · US fintech (anonymized)

Enterprise BI Platform Migration

Replaced a six-figure proprietary BI stack with self-hosted Apache Superset — plus an AI query layer.

286
tiles migrated
$0
license cost
Cell-for-cell
validated
Role
Lead engineer & architect
Client
US fintech (anonymized)
Year
2026
Lane
AI & Data Platform

The problem

A fintech's analytics ran on a proprietary BI platform with an annual license that scaled with every new seat and board. Leadership wanted the same dashboards, on the same Snowflake data, without the bill — and ideally a way to just ask questions in plain English.

What I built

A full migration onto Apache Superset: I rebuilt the CEO liveboards tab-for-tab and validated the numbers cell-for-cell against source tables. I reverse-engineered the old platform's private API to capture every tile, shipped a custom Superset image with Snowflake, SSO, and an MCP natural-language layer, and deployed the whole thing to the company's EKS platform with Terragrunt, Karpenter autoscaling, and Helm.

Outcome

Same analytics, zero license cost, running on infrastructure the company already owned — with an AI layer that lets non-analysts query the warehouse in natural language.

Stack
Apache Superset 6.1SnowflakePythonPostgreSQL 16Valkey / CeleryEKSTerragruntKarpenterHelmExternal SecretsMicrosoft Entra SSOMCP

Client identity anonymized under NDA. Numbers and architecture are real; only names and data are withheld.

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