Skip to content

Services

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

Every engagement comes with CI/CD, tests, contracts, documentation, and a handover plan by default. No black boxes, no hostage data.

Greenfield Data Platform Build

End-to-end modern stack — Snowflake, dbt, Dagster, 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, BI — all wired together with Terraform-managed RBAC and GitHub Actions CI/CD.
    • Reference dbt project with a tested staging / intermediate / marts pattern and pre-merge model contracts.
    • Self-serve BI with documented metrics from day one.
    • Operating runbook + 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 / sources in hours, not weeks.

Indicative tech: Snowflake · :simple-dbt: dbt · :simple-dagster: Dagster · Terraform · AWS · GitHub Actions

Talk to me 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

    • AWS DMS → SQS → Lambda → Snowpipe ingestion blueprint, sized to your tenant count and change volume.
    • Optional migration to Apache Iceberg with Polaris catalog to escape per-byte warehouse pricing on cold ingestion.
    • Data contracts at the source-system boundary so downstream stays protected when schemas drift.
    • Test-driven pipelines with 99.9% uptime targets baked in.

  • Typical outcomes

    • 90% lower ingestion cost.
    • 80% lower transformation cost and latency.
    • 99% lower Snowflake ingestion cost after Iceberg / Polaris migration.

Indicative tech: DMS · :simple-amazonsqs: SQS · :simple-awslambda: Lambda · Snowpipe · :simple-apacheiceberg: Iceberg + Polaris · PostgreSQL CDC

Talk to me 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 / Power BI) wired to the semantic layer.
    • Internal training so the business owns the definitions, not just consumes them.

  • Typical outcomes

    • Ad-hoc metric-definition requests down ~90%.
    • 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 · :simple-dbt: dbt · Metabase · Power BI

Talk to me about a semantic layer

FinOps & Open-Table-Format Migrations

Cut warehouse spend by 50–99% without sacrificing performance — and modernise your storage layer while you're at it.

For teams whose Snowflake / Databricks bill is climbing faster than data volume, or who want to escape per-byte warehouse pricing on cold or rarely-queried data.

  • What you get

    • Warehouse / query / model-level cost audit with prioritised remediation plan.
    • Warehouse tuning, query rewrites, and model refactors for sub-minute rebuilds.
    • Selective migration of pipelines to Apache Iceberg with Polaris catalog.
    • FinOps dashboards so spend stays controlled after I leave.

  • Typical outcomes

    • 50% Snowflake compute reduction while increasing model count.
    • 99% ingestion cost reduction on pipelines moved to Iceberg.
    • Sub-minute rebuilds on multi-billion-row fact tables.

Indicative tech: Snowflake · :simple-apacheiceberg: Iceberg + Polaris · :simple-dbt: dbt · AWS

Talk to me about FinOps

AI-Accelerated Delivery

Multi-month platform builds, compressed into single-week increments — with consistent, governed outputs.

For teams that want startup velocity with enterprise-grade quality. Either as the delivery method for the engagements above, or as a capability uplift for your existing data team.

  • What you get

    • Delivery powered by Cursor, context engineering, and skills-based agents — same patterns I use in production engagements.
    • Reusable prompts, rules, and skills tuned to your stack and conventions.
    • Optional team enablement: workshops on prompt design, context engineering, and AI-assisted code review.
    • Every AI-generated artefact still ships through full CI, tests, and contracts.

  • Typical outcomes

    • Multi-month platform builds delivered in single-week increments.
    • Predictable, repeatable outputs — no "vibe-coded" surprises in production.
    • Existing engineers shipping 3–5x faster on routine pipeline work.

Indicative tech: Cursor · Python · :simple-dbt: dbt · GitHub Actions

Talk to me about AI-accelerated delivery

How engagements work

How long are engagements?

Most fixed-scope engagements run 4–12 weeks. Greenfield platform builds are typically delivered in single-week increments with a working slice in production at the end of each week. Retainers are monthly with a 30-day 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 I built.

Security & confidentiality?

NDA-first. Enterprise-grade encryption, least-privilege access, and alignment with SOC 2 / ISO 27001 practices. Comfortable working inside existing compliance frameworks.

  • Not sure which engagement fits?

    Free 30-minute scoping call
    Recommended engagement & rough sizing
    Risk, dependencies & sequencing

    Bring your current stack, your pain points, and your timeline. I'll help you decide which of these engagements (if any) is the highest-leverage move — and give you an honest answer if it isn't me.

    Book Scoping Call