datatypes

Independent data engineering practice

Systems for data
that matters.

Datatypes designs, repairs and operates high-performance data systems. We work from the shape of the data outward: explicit invariants, bounded state, measured latency, reversible change and evidence at every boundary.

Scope
Architecture → operation
Scale
Startup → enterprise
Bias
Measured → durable
01

Practice

Engineering across the full life of a data system.

01.1

Platform architecture

Contracts, ownership and failure domains made explicit; storage and compute selected from access patterns, cardinality and change rate rather than fashion.

01.2

Pipelines and streaming

Event-time and batch systems built for idempotence, replay, late data, schema evolution and backfills that remain ordinary operations.

01.3

Performance engineering

Workload profiling from bytes to queries: layout, locality, encoding, compression and vectorised execution, with each optimisation proved against end-to-end cost.

01.4

Technical assurance

Lineage, reconciliation and deterministic recovery for systems that must explain what happened, reproduce it and correct it without losing history.

02

Fields

Specialist work, fitted to the institution.

Work spans new platforms for small teams and exacting delivery inside governments, telecommunications companies and global consultancies. In every setting, the engineering must survive incomplete data, adversarial inputs, inherited platforms and scale that does not arrive politely.

  • 01Digital assets and crypto
  • 02Government
  • 03Blockchain protocols
  • 04Artificial intelligence
  • 05Telecommunications
  • 06Consultancies

Clients range from early-stage startups to Big Four consultancies.

03

Research

Delta Sigma

Below the abstraction.

Datatypes is informed by Delta Sigma, an independent mathematics research company investigating extremely low-level solutions to fundamental computational problems.

The work reaches beneath formats and frameworks into algorithmic information, compression, ordering and the structures that determine how little computation a problem should require.

Visit Delta Sigma
04

Method

A small set of working rules.

  1. 01

    State the invariant before the implementation.

  2. 02

    Model the shape before choosing the format.

  3. 03

    Make replay and recovery ordinary.

  4. 04

    Measure the entire path, not a convenient stage.

Correctness is specified. Performance is measured. Complexity must earn its place.