Services

We run fixed-scope, outcome-priced engagements focused on shipping production-grade data platforms in weeks. We have four productised offers. Pick the one that matches where you are now, or combine them into a phased programme.

Greenfield data platform build

An end-to-end modern stack of Snowflake, dbt, Dagster and Terraform, production-ready in weeks, not quarters.

For teams without a real data platform, or stuck on spreadsheets and brittle ad-hoc pipelines.

What you get

• Cloud warehouse, orchestration, transformation and BI, all wired together with Terraform-managed RBAC and GitHub Actions CI/CD.
• Reference dbt project with a tested staging, intermediate and marts pattern and pre-merge model contracts.
• Self-serve BI with documented metrics from day one.
• Operating runbook and handover so your team owns it.

Typical outcomes

• CEO/CFO reporting from two-week cycles to real time.
• Total platform cost as low as ~$200/month at startup scale.
• Onboarding new engineers or sources in hours, not weeks.

Indicative tech: Snowflake · dbt · Dagster · Terraform · AWS · GitHub Actions

Talk to us about a platform build

Multi-tenant ingestion at scale

Re-architect CDC ingestion across thousands of tenant schemas without breaking the bank or the SLAs.

For multi-tenant SaaS platforms with sprawling source databases (hundreds to thousands of tenants), where ingestion cost and latency have started to dominate the platform bill.

What you get

• An AWS DMS to S3 to Snowpipe ingestion blueprint, sized to your change volume rather than your tenant count.
• Consolidation of the estate into one table per entity with a tenant identifier, so the warehouse prunes partitions instead of scanning a union of thousands of objects.
• A reconstruction layer that turns the CDC change stream into queryable state, parallelised so it stays inside minutes at scale.
• Data contracts at the source-system boundary so everything downstream stays protected when schemas drift.

Typical outcomes

• 90% lower ingestion cost.
• 80% lower transformation cost and latency.
• ~3 minutes from source change to queryable table, on estates where it had been 30 to 60.

Indicative tech: AWS DMS · S3 · Snowpipe · Snowflake · PostgreSQL CDC · Python

Talk to us about ingestion

Semantic layer & metrics governance

One source of truth for every metric, backed by docs, contracts and self-serve BI.

For organisations where executives still argue about whose number is right, and the data team is drowning in ad-hoc “what does X actually mean?” tickets.

What you get

• Snowflake-native semantic layer with documentation-backed metric definitions.
• Metric-level access controls and lineage from source to dashboard.
• Self-serve BI rollout (Metabase or Power BI) wired to the semantic layer.
• Internal training so the business owns the definitions rather than only consuming them.

Typical outcomes

• Ad-hoc “what does this metric mean?” requests largely disappear.
• 500+ metrics governed in a single place; 30% of the business self-serving within months.
• Full transparency and trust in board-level numbers.

Indicative tech: Snowflake Semantic Layer · dbt · Metabase · Power BI

Talk to us about a semantic layer

FinOps & cost observability

Cut warehouse spend by 50–90% without sacrificing performance, and keep it down after we have gone.

For teams whose Snowflake or Databricks bill is climbing faster than the data volume that justifies it.

What you get

• A cost audit at warehouse, query and model level, with a prioritised remediation plan.
• Warehouse tuning, query rewrites and model refactors for sub-minute rebuilds.
• Incremental model patterns so pipelines process what changed rather than everything.
• Budgets, resource monitors and cost dashboards, with alerting before a bill becomes a surprise rather than after.

Typical outcomes

• 50% Snowflake compute reduction while increasing model count.
• Sub-minute rebuilds on multi-billion-row fact tables.
• Spend that stays controlled once the engagement ends, because the budgets, monitors and alerts keep running without us.

Indicative tech: Snowflake · dbt · AWS · Snowflake Budgets & Resource Monitors

Talk to us about FinOps

How we deliver

Single-week increments are a claim about discipline, not about heroics. Every engagement runs the same way:

• Specification before code. Interviews first, then a written spec, then work broken down until each piece is small enough to describe precisely. That is what makes it small enough to finish and verify inside a week.
• Tests before implementation. Red, green, refactor. A model that ships has a failing test behind it that now passes.
• Contracts and CI on everything. Producers publish versioned schemas, breaking changes fail CI before production, and no artefact reaches a client system without passing the same gates.
• A feedback loop that closes weekly. The increment is reviewed against the spec at the end of each week, so a wrong assumption costs a week rather than a quarter.

The longer version is on our About page.

How engagements work

How long are engagements?

Most fixed-scope engagements run 4–12 weeks. We typically deliver greenfield platform builds in single-week increments, with a working slice in production at the end of each week. Retainers are monthly with 30 days’ notice.

How is pricing structured?

Engagements are outcome-priced against a written scope, not hourly. You know the price and the deliverables before you sign. Retainers are flat monthly fees with agreed hours / SLA.

Do you work with my existing team?

Yes. Most engagements include mentoring and handover by default. The goal is always to leave your team owning, operating and evolving what we built.

How do you deliver that fast?

Specs before code, tests before implementation, contracts and CI on every change, and a human review gate before anything reaches your systems. We use an AI-assisted development workflow inside those controls, as most engineering teams now do. The controls are the part that matters. They are what make the output predictable rather than merely fast, and they apply identically regardless of how a given artefact was produced. Nothing ships that has not passed the same tests, contracts and review as everything else.

Security & confidentiality?

We sign an NDA before the engagement begins, work under least-privilege access to your systems, and operate inside whatever security and compliance frameworks you already have.