Services

Data platforms that
earn their keep.

Six engagements I take on — each with defined deliverables, not open-ended retainers.

Data Architecture & Governance

Enterprise data strategy and the governance scaffolding that keeps it honest as teams multiply.

Deliverables

  • Target-state architecture
  • Governance framework
  • Data catalog design
  • Privacy & compliance map
  • Roadmap

Lakehouse Implementation

Medallion architecture on Databricks with Unity Catalog governance, built to production standards from the first commit.

Deliverables

  • Bronze/silver/gold pipelines
  • Unity Catalog setup
  • Data quality expectations
  • Validation SQL
  • Runbook

Cloud Migration

Moving data estates to AWS, Azure or OCI without the six-month surprise. Baseline first, then migrate.

Deliverables

  • Current-state assessment
  • Migration plan & waves
  • Cost model
  • Cutover & rollback plan

Database Engineering

Oracle, PostgreSQL and SQL Server work: performance tuning, high availability and capacity planning under real load.

Deliverables

  • Performance baseline
  • Tuning changes
  • RAC / Data Guard design
  • Capacity forecast

Analytics & BI Architecture

Dimensional models and Power BI architecture so self-service actually stays trustworthy.

Deliverables

  • Dimensional model
  • Semantic layer
  • Executive KPI set
  • Self-service guardrails

AI-Enabled Automation

Targeted AI where it removes measurable admin load — document review, completeness checks, exception triage.

Deliverables

  • Use-case assessment
  • Prototype
  • Human-in-loop design
  • Evaluation harness

For football

Data your club can trust on matchday.

I referee on weekends and build registration and compliance data for football clubs through Let's Data Talk. Football data has its own rhythm: seasons, transfers, age groups and volunteers. I design for it.

Clubs

Match, player and membership data in one governed place: registrations that reconcile, rosters coaches can rely on and reporting the board can defend.

Federations

Registration, competition and participation data across every member club, with shared standards, compliance reporting and one source of truth.

Talk football data

Process

How an engagement runs.

1

Discovery

Stakeholder interviews, current-state audit and a written baseline. No recommendations until the numbers exist.

2

Design

Target architecture, integration options, trade-offs and risks — documented so your team can challenge it.

3

Implement

Build in production-shaped increments with data quality rules, validation and handover docs from the start.

4

Optimise

Tune against the baseline, close the gaps, transfer ownership. Success means you don't need me next quarter.

Why me

Why work with me.

20+ years, four countries

IBM, INDRA, DIRECTV LATAM, University of Otago, Fronde and QUT. I've seen how the same architecture fails differently in different regulatory contexts.

Measured outcomes

70% performance improvement through capacity planning at Fronde. 30% faster query execution at DIRECTV supporting 3M+ users. Numbers, not adjectives.

Both sides of the wall

I've run the databases at 2am and written the three-year strategy. Architecture that ignores operations isn't architecture.

Documentation that ships

Constraints, integration options, compliance considerations and recovery notes — written so the next engineer doesn't reverse-engineer your platform.

Vendor-neutral

Certified across AWS, Azure, Oracle Cloud and Databricks. No incentive to sell you the platform I happen to resell.

Founder's perspective

I run my own product, Let's Data Talk. I know what it costs to maintain the thing after the project closes.

Start a conversation →