About
A senior-led practice, deliberately small.
Intellora Tech is an engineering consultancy working across data, cloud, AI and security. A collective of specialists — database, cloud, analytics, machine learning, governance and security — led by a principal engineer who staffs each project and reviews what ships. You speak to hands-on engineers throughout, never an account manager.
How we stay small on purpose
A capped book is the quality control.
We run at most three projects concurrently. Not as a scarcity tactic — as the only honest way to promise that the specialists on your platform are genuinely thinking about it, and that the principal can review every piece of work rather than signing off work nobody senior has read.
We decline
Work outside our depth, scope that is genuinely undefined at contracting, and deadlines that would force us to cut the testing or the documentation.
We finish
A project is done when it is documented, handed over and running — not when the hours are used up. Overrun on a fixed price is our problem, not yours.
We go narrow
One capability, delivered completely, beats a broad project delivered to eighty per cent. If the right answer is a smaller project, we will propose the smaller one.
Principal engineer · practice lead
Musisi Ntege Simon Peter
Leads the practice: sets the engineering standards, staffs each project, and reviews what goes out the door. Roughly a decade of production data engineering across core banking, United Nations humanitarian operations, and revenue and customs administration.
Deepest personally in Oracle database internals, enterprise data warehouse architecture and ETL and ELT engineering. Holds an MBA and a BSc in Computer Engineering.
Certified in
Specialists, matched to your stack
No single engineer is deepest at everything, and we do not pretend otherwise. The practice is organised around distinct specialisms, and a project is staffed with the people whose depth matches the work rather than whoever is free.
Database engineering
Oracle internals, PostgreSQL, SQL Server and MySQL. Modelling, tuning, high availability, migration and Oracle Data Integrator.
Cloud & platform
AWS architecture, landing zones, infrastructure as code, CI/CD for data infrastructure, and cost engineering.
Analytics engineering
Semantic modelling, dbt, Oracle Analytics and Power BI, and the metric governance that stops dashboards disagreeing.
Machine learning
Feature pipelines, training workflows, MLOps and retrieval systems — built by people who ship models, not only notebooks.
Governance & data quality
Lineage, cataloguing, quality enforcement and the evidence trail an auditor or regulator will eventually ask for.
Platform security
Access control design, encryption and key management, secrets, and audit logging for the data estate.
How a distributed practice works
Weekly written update
Every Friday from the engineer leading your work: what shipped, what is next, what is blocked, and any change to the estimate — in writing, so it survives being forwarded to your board.
Working sessions, not status calls
Calls are for decisions and joint work. Status arrives in writing beforehand so the call is not spent reading it aloud.
Your tools
The team works in your Slack, your Jira, your repository and your cloud account, with access provisioned at least privilege and revoked on handover.
Handover as a piece of work
Documentation, runbooks and decision records, plus a live session between your engineers and ours — so the work outlives the project.
Work with the engineers, not the org chart.
One paragraph about what is broken is enough to start.