Platform Consulting

A data platform isn’t a website. You can’t go and look at it. You can’t show it to a board. It’s backend infrastructure — invisible to most of the business — and yet the decisions made at the start determine whether it delivers value for years or becomes an expensive problem to unpick.

That’s where consulting comes in. Before you commit budget to building anything, you need a clear picture of what you’re building, why, and with what team.

Platform strategy and vendor selection

AWS native, Databricks, Snowflake — each has a different cost model, a different engineering overhead, and a different ceiling. We assess your data estate, your existing infrastructure, and your roadmap, then give you a recommendation you can take to a CFO. Not a shortlist. A recommendation.

Architecture review and design guidance

We explain what medallion architecture, lakehouse, and data mesh actually mean for your specific situation — not in the abstract. We map out what a well-designed platform looks like for your data volumes, your sources, and your consumers. You leave with a blueprint, not a presentation.

Current state assessment

Most organisations asking about data platforms already have something — a database, a set of reports, a collection of point-to-point integrations. We assess what you have, identify the gaps and risks, and tell you what’s worth keeping and what isn’t.

Operating model and team design

A data platform needs people to run it once it’s built. For a small buildout where the client already has an Ops team, a single Senior Data Engineer is often enough — given access to S3 and a Databricks licence, one strong engineer can deliver and own the platform. For larger programmes, the team typically includes a Principal Data Engineer, a DevOps Engineer with data platform experience, and a Data Governance lead.

We help you understand what each role actually does, what to look for when hiring, and whether contractors or permanent staff make more sense for each phase.

What a data platform actually is

The simplest way to think about it: a data platform is what a database grows into when your data becomes too large, too varied, or too valuable to keep in one place. Databases handle structured data — rows and columns, clean and consistent. A data platform handles everything else too: unstructured files, streaming events, API outputs, logs. It separates storage from compute. It makes data available to multiple consumers — analytics teams, AI models, operational systems — without each one pulling directly from the source.

How we work

We fit into your existing delivery framework — Scrum, Kanban, or whatever your organisation runs. A consulting engagement typically produces: a current state assessment, a platform recommendation with rationale, a high-level architecture, a team design, and a prioritised roadmap. Everything documented, everything owned by you.