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DataHorizon
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Company

The consultants who design, build and hand over the systems behind your decisions.

DataHorizon is led by two Auckland-based principals who combine data engineering, BI, AI and financial modelling into one delivery team. We do not just advise: we architect the system, embed with your people, and leave you with a governed capability that keeps working after we are gone.

18+ years
Combined principal experience
6 industries
Operating contexts delivered
Strategy to delivery
Principal involvement

Principals

Technical depth, commercial judgement and accountable leadership.

Mohit Saini

Auckland, New Zealand

Co-Founder & Principal Consultant — Data, AI & BI Systems

Mohit founded DataHorizon to close the gap he kept seeing inside enterprises: strong appetite for analytics and AI, but no engineered system underneath it. He works end to end — from ingestion and governance through semantic models, predictive services and the web applications decision-makers actually open every morning.

His delivery background spans port logistics, insurance, agritech and professional services, working alongside internal data teams rather than around them. Engagements typically start with a diagnostic of the existing estate, then move quickly to a production-grade slice that proves the architecture before it scales.

He remains hands-on in every engagement: writing the DAX, shaping the Fabric pipelines, reviewing the TypeScript. Clients deal with the engineer who designed the system, not an account layer above it.

Credentials

  • Architects end-to-end data, BI and AI systems that survive real operational load
  • Designs governed semantic layers and metrics so reports agree across the business
  • Builds predictive services and automation that plug into daily workflows
  • Delivers decision-ready web applications — not just dashboards — for operational teams
  • Runs diagnostic-to-production engagements that prove value before scaling spend
  • Works as an embedded senior engineer alongside client data teams

Delivery experience

9+ years
Professional experience
Auckland
Base

Working stack

  • Microsoft Fabric
  • Power BI
  • DAX
  • SQL
  • dbt
  • Azure
  • Python
  • TypeScript
  • React
  • AI / LLM APIs

Teo McArthur

Auckland, New Zealand

Co-Founder & Principal Consultant — BI Strategy, Finance & Transformation

Teo helps leadership teams stop running the business on spreadsheet opinions and start making decisions from one governed, repeatable source of truth. His work sits at the intersection of finance, operations and BI — translating board-level questions into reporting that analysts can maintain and executives can trust. He is a CFA Level I candidate, with the accounting, valuation and investment rigour that underpins his financial modelling work.

Across infrastructure, investment management, retail and financial services, he has led organisation-wide Power BI rollouts, replaced fragile Excel workflows with SQL-backed reporting, and built valuation, forecasting and investment models that shape capital and operational decisions.

He combines strategy with implementation detail: he can design a multi-year reporting roadmap and governance model, then sit with analysts to make the measures, DAX patterns and data flows stick. The result is a finance and BI capability that keeps working after the consultants leave.

Credentials

  • Turns ambiguous financial and operational questions into governed, auditable reporting
  • Leads BI transformation from strategy through analyst adoption and governance
  • Builds valuation, forecasting and investment models for capital and operational decisions
  • Standardises metrics and DAX practices so Power BI estates stay consistent
  • Migrates spreadsheet-based reporting into SQL-backed systems with integrity controls
  • Bridges executive priorities and delivery teams without losing implementation detail

Delivery experience

9+ years
Professional experience
Auckland
Base

Working stack

  • Power BI
  • DAX
  • SQL Server
  • PostgreSQL
  • Azure
  • Excel
  • Financial modelling
  • Forecasting
  • AI workflows

Practice leadership

Three delivery practices, one accountable team.

Data Engineering & Governance

Ingestion, modelling, lineage and governance in Microsoft Fabric and SQL estates

Lakehouse and warehouse design, incremental pipelines, data quality gates, lineage documentation and role-level security models that survive audit.

  • Medallion architectures in Microsoft Fabric
  • Automated data quality and reconciliation testing
  • Row-level and object-level security design
  • Fabric
  • Dataflows Gen2
  • SQL
  • Python
  • Great Expectations

AI & Predictive Modelling

Forecasting, classification, document intelligence and process automation

Models are built to be operated: versioned, monitored, and wired into the workflow that consumes them rather than parked in a notebook.

  • Demand and utilisation forecasting in production
  • Document extraction and claims triage automation
  • Model monitoring and drift alerting
  • Python
  • scikit-learn
  • Azure ML
  • LLM APIs

Intelligent Web Applications

Internal tools, client portals and PWAs on a typed, testable stack

Decision tooling built as real software: typed end to end, access-controlled, instrumented, and deployable on a weekly cadence.

  • Operational portals replacing spreadsheet workflows
  • Progressive Web Apps for field and warehouse teams
  • Role-based access with row-level security
  • React
  • TypeScript
  • Vite
  • Tailwind
  • Supabase

Talk directly to the principals who will lead it.

Book a short intro call or a longer scoping session — no sales layer, just a practical conversation about the decision, the data and the path to delivery.