Senior Data Architect

About OB Collective

OB Collective is a UK technology business working on independent verification, data integrity and evidence for information moving between organisations and systems. We work primarily in government and regulated environments, combining software engineering, data architecture and assurance to make information easier to exchange, understand and verify.

Role: Data Architect

We're looking for an experienced Data Architect with strong IES, semantic data and ontology expertise to join an initial five-month technical programme focused on integrating operational policing information across different force environments.

Programme Overview

The programme will explore how information from locally configured source systems can be acquired, mapped and aligned into a common semantic model while preserving source provenance, meaning and uncertainty. The work will contribute to an evolving Information Exchange Standard and help establish a repeatable pattern that can be adopted by additional forces and suppliers.

You will work closely with solution architects, data engineers, API engineers, security specialists and policing SMEs. The role is highly practical: we need someone who can move between semantic-model design, source-to-target mapping, ontology decisions, validation and executable tests.

Responsibilities

• Lead semantic modelling and ontology work across the programme.
• Interpret and work with the Information Exchange Standard and emerging policing/justice extensions.
• Define source-to-IES mappings for operational policing information.
• Support the evolution of IES profiles where source concepts do not map cleanly to the existing model.
• Define how entities, relationships, identifiers and provenance should be represented.
• Establish validation approaches for aligned data using appropriate semantic technologies.
• Design repeatable mapping and regression tests.
• Support entity-resolution and record-matching design, including ambiguity and confidence.
• Ensure semantic transformations preserve source lineage and do not introduce false certainty.
• Define how reference data, code lists and lookup datasets are versioned and represented in transformation provenance.
• Work with engineers on machine-readable mappings, schemas, profiles and transformation rules.
• Help determine how semantically equivalent representations should be compared and validated.
• Support bounded extraction of entities from unstructured or narrative source data where relevant.
• Contribute to the programme's interoperability and conformance test suite.
• Document semantic assumptions, modelling decisions and areas requiring further Beta work.
• Help make the resulting pattern understandable and reusable by future forces and suppliers.