About
I build the connective tissue between systems, data, and the people who use them.
I work independently as a technical specialist across software integrations, cloud automation, data engineering, and business intelligence. Most of what I build is unglamorous by design: services that run on schedule, data that reconciles, and reports that stay correct without anyone tending to them.
Approach
Hands-on, end to end.
I prefer to understand a process before changing it. That usually means sitting with the people who run it today, following the data through every hand-off, and finding where it is re-keyed, re-formatted, or quietly lost.
From there I design the smallest system that solves the problem properly: a clear data model, well-behaved integrations, explicit handling for the cases that will go wrong, and reporting that reflects definitions everyone has agreed on.
I stay involved after delivery. Systems that touch live business operations reveal their real requirements only once they are running, and I would rather refine something into genuinely low-maintenance shape than hand over and disappear.
Focus areas
Where I spend my time
API integrations and authentication
Connecting platforms over REST and webhooks, handling OAuth and token lifecycles, rate limits, retries, and the awkward edge cases that only appear in production.
Cloud systems and serverless deployments
Containerised services on Cloud Run, scheduled jobs, message-driven processing, secrets handling, and deployments that stay simple enough to reason about.
Relational data design and data pipelines
PostgreSQL and Cloud SQL schemas designed around real business entities, with ingestion, transformation, and quality checks that keep the record trustworthy.
CRM and workflow automation
Zoho CRM, Creator, and Analytics builds alongside Power Platform and Microsoft cloud automations, replacing manual steps with rules people can inspect.
Dashboards and operational reporting
BigQuery and PostgreSQL reporting models, agreed KPI definitions, and stakeholder views built for daily operational use rather than for a one-off presentation.
Practical use of AI in business processes
Document extraction, structured research, and drafting workflows with defined schemas, retained sources, and human review before anything is accepted.
Principles
Working principles
The standards I hold myself to on every engagement.
- Reliability
- A system that mostly works creates more work than none at all. I design for failure paths, retries, and visibility from the start.
- Ownership
- I take responsibility for the whole path from source system to the report someone opens, not only the part that is convenient to build.
- Clarity
- Plain explanations, documented decisions, and data models that a non-specialist can follow when they need to.
- Security
- Least-privilege access, credentials kept out of code, minimum necessary data, and explicit scopes for anything touching third-party accounts.
- Maintainability
- Straightforward, conventional solutions that the owner can keep running, extend, or hand to someone else without archaeology.
- Practical outcomes
- Success is measured by manual work removed and decisions made more easily — not by how much technology was involved.