Semantic Layer Engineering
Versioned metric definitions in dbt Semantic Layer, Cube, or LookML: one source of truth every renderer consumes.
Data & AnalyticsBusiness Intelligence
BI that turns dashboards into decisions
Senior BI engineering (semantic-layer dashboards, modern data stack, lineage-evidenced metrics), engineered to replace the Excel + Power BI fragmentation with one source of truth your board actually trusts.
0 defPer metric, across the firm
<0 wksTo first semantic-layer metric
0%Less stakeholder spreadsheet drift
What we build
Business intelligence services we deliver end-to-end
Pick a single capability or compose them into a full BI programme. Every engagement runs through the same metric-governance, lineage, and adoption gates.
- Semantic layer firstOne governed definition of every metric.
- Metric governanceCertified metrics, named owners, and change control.
- Self-serve, governedAnalysts explore freely inside clear guardrails.
- Adoption focusedBuilt for the people who make the decisions.
Governed BI Platform
Semantic Layer Engineering
Versioned metric definitions in dbt Semantic Layer, Cube, or LookML: one source of truth every renderer consumes.
Decision Dashboards
Power BI, Tableau, and Looker dashboards built against the semantic layer, decision-grade, not impression-grade.
Embedded Analytics
Customer-facing analytics surfaces, partner portals, and white-label data products powered by your warehouse.
Metric Governance
Definition ownership, change-control, deprecation policy, the BI workflow that ends the war over numbers.
Self-Service BI
Certified datasets, governed workspaces, and analyst enablement that scales BI beyond the central team.
AI-Generated Narratives
LLM-generated explanations grounded in your semantic layer: exec summaries and alert context, hallucination-managed.
How we deliver
Our streamlined BI delivery lifecycle
Seven stages from metric audit to enterprise-scale BI. Every engagement runs through the same gates, with metric ownership and adoption measured from day one.
- 01
Audit
Audit dashboards and conflicting metric definitions.
- 02
Design
Design semantic layer and metric catalogue.
- 03
Build
Stand up warehouse, dbt project and semantic layer.
- 04
Render
Build dashboards against the semantic layer.
- 05
Govern
Versioned definitions, change-control and RBAC.
- 06
Enable
Train self-serve users with governance guardrails.
- 07
Scale
Embedded analytics, AI narratives and warehouse FinOps.
Capabilities
Four capabilities behind every BI engagement
Each tab below shows what production-grade looks like for a different layer of the BI stack. Pick the one closest to your current bottleneck.
Semantic Layer
One definition of every metric, version-controlled
dbt Semantic Layer, Cube, or LookML: versioned, lineage-evidenced metric definitions owned by data engineering and consumed by every renderer.
Single source of truth Revenue, churn, active users: one definition that Power BI, Tableau, and your finance team all consume.
Lineage & change-control Every metric carries column-level lineage and a PR-reviewed change history.
Renderer-agnostic Swap dashboards tomorrow: the metric definitions don't move.
Tested by default dbt tests, freshness SLAs, and schema-change alerts on every definition.
Our engagement workflow
Seven stages from first call to ongoing support
Every engagement walks the same path, sized to your problem, but with the same verification gates baked in.
Phase 01Discovery
Two-week paid sprint. Architect-led. Output: regulator map, costed roadmap, signed scope.
Phase 02Planning
Pod composition, sequenced milestones, change-control governance, and risk register.
Phase 03Design
Reference architecture, threat model, design system, and acceptance criteria locked.
Phase 04Development
Weekly demos, trunk-based, CI/CD from day one. Code reviewed against spec at every gate.
Phase 05Testing
Unit, integration, e2e, security, performance, and accessibility, automated and gated.
Phase 06Deployment
Blue-green or canary, observability live before launch, rollback rehearsed.
Phase 07Support
Managed services or hypercare hand-off. Defined SLOs, named on-call, monthly reviews.
Success stories
Programmes we have shipped
44%
Banking
AML transaction-monitoring analytics for a bank
Cut false-positive AML alerts 44% at a bank while catching more genuine risk.
SnowflakedbtPythonPower BI
Country · UK
60→1
Insurance
Underwriting analytics dashboards for an insurer
Replaced 60 spreadsheets with one governed underwriting board pack for an insurer.
Power BITabularAzuredbt
Country · UK
3x
Foodtech
Self-service analytics for a foodtech platform
Self-service models tripled analyst throughput at a food-delivery platform.
LookerdbtBigQuery
Country · FR
24%
Telemedicine
Patient 360 for a telemedicine provider
Unified a fragmented patient view, lifting care-team efficiency 24% at a telemedicine provider.
SnowflakedbtPower BIFHIR
Country · UK
live
Fintech
Loss and fraud analytics for a fintech
Live loss-and-fraud analytics replaced a two-day report at a fintech, surfacing emerging fraud same-day.
dbtBigQueryLookerFivetran
Country · UK
60%
Retail
Lakehouse build for a grocery retailer
Unified 40 sources into a governed lakehouse, cutting report build time 60% for a grocery retailer.
DatabricksDelta LakeSparkTerraform
Country · UK
sub-second
Logistics
Real-time data pipeline for a logistics operator
Delivered sub-second track-and-trace event data to 30 teams for a logistics operator.
KafkaFlinkIcebergKubernetes
Country · DE
100%
Pharma
Data governance and catalogue for a pharma manufacturer
Catalogued and lineage-traced 100% of GxP-regulated data domains for a pharma manufacturer.
CollibradbtSnowflakeOpenLineage
Country · CH
45%
Automotive
Cloud warehouse migration for a carmaker
Migrated a legacy warehouse to the cloud, cutting query cost 45% for a carmaker.
SnowflakedbtFivetranTerraform
Country · DE
38%
Healthcare
Claims and billing analytics for a hospital group
Unified claims and billing data, cutting rejected-claim rework 38% for a hospital group.
SnowflakedbtFHIRPower BI
Country · UK
Who we are
About usBritonOne Technology is a full-cycle engineering company that builds and operates production software for regulated estates. Since 2017, we have shipped programmes that clear audit on the first pass across banking, insurance, wealth, healthcare, and biotech. Our teams pair deep domain knowledge with disciplined engineering, treating compliance, security, and resilience as first-class deliverables. From architecture through to live operations, we stay accountable for the systems we build, measuring success by uptime, audit outcomes, and defensible business results.
60+Senior engineers across UK and EU
Why choose us
Engineer experience, average9+ yrs
Specialist replacement window48h
Code and IP ownership, day one100%
Surprise invoicesZero
Why teams choose BritonOne Technology
Four reasons enterprise buyers come back
We don't compete on lowest day-rate. We compete on shipped outcomes inside environments that have to clear audit.
Senior-only delivery
Every engineer on every engagement is at least senior, typically eight to fifteen years deep in their craft. No bench rotations, no junior pyramid hidden behind a glossy proposal, no bait-and-switch after contract signature. The architect who scoped your engagement is the same person committing code by week three.
Audit-ready by default
FCA, PRA, EBA, BaFin, FINMA, HIPAA, SOC 2 Type II: every framework we work under is treated as a design constraint from day one, not a final-stage gate. Evidence trails, model-risk packs, change-control artefacts, and pen-test reports ship alongside the code, ready for second-line review without a remediation sprint.
Anti-drift delivery discipline
Small pods of three to seven engineers, each with a named delivery lead who owns scope, schedule, and outcomes from kickoff to hand-off, never a faceless team you have to chase for an answer. Weekly demos run against the signed scope, frequent verification gates catch regressions early, and quarterly outcome reviews measure real progress against the original business case rather than a moving target. Together those rituals catch scope drift before it has any chance to compound, so programmes that should take six months don't quietly stretch into eighteen, budgets stay anchored to what was agreed, and every milestone ships with a written, testable definition of done that both sides sign off before we move on.
Long-tail support beyond hand-off
We don't disappear the moment the engagement closes. Managed services, hypercare windows, named on-call rotations, or quarterly health checks: pick the depth that matches your operational risk profile. About seventy percent of clients return for a second programme, usually because the team that shipped the first one is still on the other end of the page.
Client Satisfaction Reviews
Words from the teams we have shipped with.
Anonymous under MNDA. Each quote is from a senior buyer who owned the engagement end to end across the services catalogue.
One Team Replacing Two Vendors
“BritonOne Technology replaced two of our incumbent vendors with one team. Faster sprints, fewer status meetings, more code shipped per week.”
VP EngineeringTier-1 European retail bank
Common pre-engagement questions
Things buyers ask before picking the first service
