Hands-on analytics engineering
Production SQL and dbt delivery, legacy-model refactoring, dimensional modelling, automated testing, CI/CD and maintainable analytics architecture.
UK-based ยท Remote with UK and international teams
Contract analytics engineering consultant for trusted reporting
Hands-on senior delivery for the models, metrics and reporting workflows your business depends on.
I bring more than eight years of production analytics engineering experience across dbt, Snowflake, BigQuery, Looker, semantic layers and source-to-report reconciliation. I can join an existing team, stabilise a delivery gap or take on one defined reporting problem from evidence through implementation. Based in the UK, I work remotely with UK and international teams where the scope, time-zone overlap and contracting arrangements are a practical fit.
Capabilities
Delivery across the trusted reporting stack
Semantic layers and metrics
Looker and LookML development, reusable metric logic, KPI definitions, model grain, ownership, caveats and controlled business meaning.
Reporting reconciliation
Trace disputed numbers across finance, CRM, operational systems, spreadsheets, transformations and dashboards to find where they diverge.
AI-ready reporting foundations
Prepare governed metrics, source evidence, tests and safe-use context before AI or automation scales reporting logic.
Selected delivery evidence
Examples from production analytics work
The work includes transformation-estate refactoring, event-data modelling, semantic-layer delivery and multi-source reporting platforms. The summaries use generalised organisational details and focus on verifiable scope, decisions and delivery.
- Legacy dbt and Snowflake refactoring with tests, CI/CD and reusable LookML patterns.
- Nested GA4 event transformation from BigQuery into normalised Snowflake reporting models.
- An eight-source BigQuery and dbt warehouse powering unified live performance dashboards.
Technology and practice
Modern analytics engineering without losing sight of the number
Tools matter, but the outcome is not a larger codebase. It is reporting logic that is reviewable, testable, explainable and safe to change. I work across the technical stack while keeping grain, definitions, reconciliation and downstream decisions visible.
Ways to engage
Add delivery capacity or start with one defined problem
Contract delivery
Join an existing data team to deliver, refactor or stabilise production analytics work with clear ownership and review standards.
Interim support
Provide senior hands-on capacity during platform migrations, finance transformation, ERP or CRM change, and reporting recovery work.
Fixed-scope investigation
Start with one contested metric, dashboard or recurring reporting workflow when the immediate need is diagnosis and a prioritised fix plan.
Delivery approach
Move from disputed logic to maintainable delivery
Start with the decision
Clarify the decision, metric, report or workflow that matters before changing models or adding another dashboard.
Trace the evidence
Inspect sources, grain, transformations, joins, definitions, ownership, caveats and downstream use.
Deliver the change
Implement the smallest useful technical change with tests, reconciliation, documentation and normal code review.
Leave a maintainable system
Make the logic inspectable, reduce duplicated rules and give the team a clearer operating boundary for future changes.
Good fit
Useful when the reporting problem is already affecting delivery or decisions
The best starting point is a real delivery need: a model backlog, a migration, a disputed metric, a semantic-layer gap, or a reporting workflow that repeatedly consumes senior attention.
- A data team needs senior hands-on analytics engineering capacity.
- A dbt, Snowflake, BigQuery or Looker estate needs refactoring or stronger controls.
- Finance, CRM, spreadsheets and dashboards disagree about an important number.
- A semantic layer or KPI definition needs to become reusable and governable.
- An AI reporting initiative needs trusted metric foundations before it scales.
Start a conversation
Describe the delivery need or reporting problem
Share the stack, the immediate objective, the business number or workflow involved, and the capacity you need. I will reply by email if the engagement looks like a useful fit.
You do not need a finished technical specification. Start with the decision, metric, model or delivery constraint that is creating the most friction.