Company
The consultants who design, build and hand over the systems behind your decisions.
DataHorizon is led by two Auckland-based principals who bring data engineering, BI, AI and financial modelling into one delivery team. We architect the system, embed with your people, and leave you with a governed capability that keeps working after we hand it over.
- 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 ZealandPrincipal 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 ZealandPrincipal 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 where finance, operations and BI meet: he turns board-level questions into reporting that analysts can maintain and executives can trust. He is a CFA Level I candidate, and that accounting, valuation and investment grounding runs through 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
Team
The people who keep your data trusted and your engagement moving.
Teja Midamanuru
Data Governance Lead
Auckland, New Zealand
Teja helps clients put practical governance around their data without turning it into a paperwork exercise. She works with business and technical teams to clarify who owns key information, what good quality looks like, and how access should be managed.
Her focus is on governance that people can actually follow. That means bringing policies, responsibilities and day-to-day delivery together so trusted data becomes part of how the organisation works, rather than a separate compliance task.
How Teja helps
- Establishes clear data ownership and stewardship responsibilities
- Turns governance requirements into workable processes for delivery teams
- Helps organisations improve data quality, privacy and access controls
teja.midamanuru@datahorizon.nz
Puravi Shetty
Administrator and Client Coordinator
Auckland, New Zealand
Puravi is often the person making sure clients know what is happening next. She coordinates meetings, project administration and follow-ups so conversations turn into clear actions and nothing important gets lost between sessions.
She supports the team and our clients throughout an engagement, helping the work stay organised, responsive and easy to navigate from the first enquiry through to delivery.
How Puravi helps
- Coordinates meetings, documentation and client communication
- Keeps project administration and follow-ups on track
- Provides a clear point of contact for practical engagement matters
puravi.shetty@datahorizon.nzPractice 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
