Available for new engagements
Data platforms that survive contact with a real business.
Eight years owning a data warehouse and reporting function end-to-end — dbt, BigQuery, Airflow, CDC and self-serve BI. When a number looks wrong, I find out why.
Independent. No reseller commissions, no vendor incentives — the recommendation is the one I would make if I were paying for it.
Recognise any of these?
The problems I get called about
- Two reports answer the same question differently, and nobody can say which is right.
- Every new metric takes weeks and touches code nobody wants to open.
- The warehouse bill grows faster than the company does.
- Analysis still depends on one person, one spreadsheet and one laptop.
- A pipeline failed on Tuesday and you found out on Friday, from a customer.
- You are about to commission a rebuild and want a second opinion first.
Services
What I am usually hired to do
Each of these is sold on its own, with its own scope. You are not required to buy the next one.
Data stack audit
A data stack audit that tells you what to fix first.
A two-week review of your warehouse, pipelines, models and reporting layer, ending in a prioritised plan of what to fix, what to keep and what to delete.
Read moreData platform build
A data platform your team can run without me.
Design and build of the warehouse, ingestion, transformation and orchestration layers, set up so your own team can operate and extend it after handover.
Read moreAnalytics engineering
Models and metrics that agree with each other.
Turning raw warehouse tables into a tested, documented modelling layer where every metric is defined once and every number can be traced to its source.
Read moreProduct analytics
Tracking you can actually make decisions on.
Tracking plans and event instrumentation for GA4, Amplitude and the warehouse, built so product and marketing numbers reconcile instead of competing.
Read moreBI and reporting
Reporting that answers the question being asked.
Dashboards and reporting built around the decisions they support, with defined metrics, honest caveats and a maintenance model that stops dashboard sprawl.
Read moreAI-assisted data workflows
Put AI where it holds up, and nowhere else.
Repeatable AI-assisted workflows for the parts of data work that are genuinely repetitive — quality assessment, documentation, triage — with the boundaries stated explicitly.
Read moreFractional data lead
Senior data leadership, part time.
Ongoing technical leadership for companies that need senior data judgement and direction but do not yet need a full-time head of data.
Read moreSelected work
Problems that were ambiguous on arrival and provable on exit
These are from eight years owning the data warehouse and reporting function of a consumer marketplace platform, in-house rather than as an outside consultant. The employer and the internal system names are withheld; the numbers are the real ones.
In-house · consumer marketplace platform
A seven-figure block of revenue with no category attached.
After a payment platform migration, seven figures of revenue was landing without category attributes. Tracing it found a data model gap the migration merely exposed.
- Seven figures Revenue correctly attributed
- Byte-identical dev/prod parity Verification standard
In-house · consumer marketplace platform
The metric had not collapsed. Its attribution had.
A key metric appeared to fall off a cliff and stakeholders feared a real drop in user activity. The events were still arriving — they had lost their attribution upstream.
- ~75% → ~100% Completeness restored
- Backfilled unsampled History
In-house · consumer marketplace platform
The aggregate metrics did not move. The harm was real anyway.
A moderation bug degraded how some listings were shown. Aggregate engagement looked untouched because demand shifted to substitutes, so impact was measured per item.
- ~9σ Statistical confidence
- One day earlier than reported True onset
How I work
Three commitments that shape every engagement
Diagnose before building
Most stacks do not need replacing. They need three specific things fixed, in the right order. The cheapest engagement I sell is the one that tells you which three.
Built to be handed over
Version control, tests, documentation and a runbook, plus working sessions until your team is comfortable. A dependency on me is a failure mode, not a business model.
Honest about limits
If a use case is a bad fit, or the problem is organisational rather than technical, you get told that — including when it means a smaller project.
Free
The data stack audit checklist
The same checklist I work through on a paid audit: the questions to ask of your warehouse, pipelines, models and reporting layer, and what a bad answer to each one actually costs you.
Sent by email. No sequence, no drip campaign — the guide, and then the monthly newsletter you can leave at any time.
Get the checklist
Questions
What people ask before hiring me
How do engagements usually start?
With a short call to work out whether the problem is what it appears to be, and whether I am the right person for it. Where the situation is unclear, the usual first step is the fixed-scope data stack audit, which ends in a ranked plan you are free to execute with your own team.
Do you work with our existing team, or instead of them?
With them, in almost every case. Work built alongside the people who inherit it gets maintained; work delivered over their heads gets quietly replaced. Where a real capability gap exists, the honest recommendation is a hire, and I will help you make it.
What does it cost?
Fixed-scope work is quoted as a fixed fee before it starts, so there is no meter running. Ongoing work is a monthly retainer against agreed availability. Both are scoped on the call, because a number quoted before understanding the problem is either padded or wrong.
Which tools and platforms do you work with?
Cloud warehouses such as BigQuery, Snowflake, Redshift and Postgres, transformation in dbt and SQL, orchestration in Airflow, Dagster or managed schedulers, and the common BI tools. The default is to work with what you already own — a migration has to earn its place.
Are you available right now?
Availability changes month to month. The fastest way to find out is to ask on the call, and if there is a wait I will say so rather than hold a slot open.
Tell me what is broken.
A short call is usually enough to tell whether this is a two-week fix or a two-month one — and whether I am the right person for it.