AI requires
AI-grade data.
Your current architecture
is a liability.
HPDL builds reliable, metadata-driven data pipelines for organisations that need Databricks, Snowflake and Azure Fabric to actually deliver.
Built for modern data platforms
The 4 Extremely High Priority Problems
These are the problems that keep decision makers awake at night. High Performance Data Logistics is built to solve them at the root.
AI Starvation
AI initiatives stall because the data layer isn’t ready. Models wait. Pilots fail. Competitive ground is lost.
HPDL fixes the data foundation so AI can actually move.
Decision Distrust
Leaders cannot trust the numbers they’re given. Reports conflict. Decisions slow down or go wrong.
HPDL builds reliable, observable pipelines that produce numbers you can stand behind.
Compliance Exposure
Sensitive data moves through opaque pipelines with weak controls, poor lineage, and limited auditability.
HPDL makes data movement visible, controlled, and defensible.
Silent Failure
Bad data reaches customers, operations, or regulators before anyone notices. Damage is already done.
HPDL detects, contains, and repairs data issues before they become business problems.
The visible symptom
Spiraling costs and diminishing returns.
Cloud bills climb while delivery slows. The four problems above are the root cause — cost is what leadership sees first.
The solution
High Performance Data Logistics.
Idempotent pipelines. Metadata you can trust. Continuous quality monitoring. Data that is ready for AI, safe for decisions, and defensible under scrutiny.
What we deliver
Focused, high-leverage engineering — not another generalist consultancy.
Data FinOps Remediation
A strict two-to-three-week technical sprint to slash your compute costs across Azure, Snowflake, Databricks, BigQuery, and Redshift. Stop paying for assessments—start recovering cash.
- • Self-funding execution sprint
- • Immediate compute cost reduction
- • Value-based pricing
Idempotent Pipeline Rebuild
Design and implement production-grade, re-runnable pipelines with proper state management, late-arriving data handling and clear contracts.
- • Exactly-once / at-least-once patterns
- • Schema evolution handling
- • Observability & alerting built in
Metadata & AI-Ready Layer
Build the metadata, lineage and semantic layer that turns raw platform data into reliable inputs for analytics and AI teams.
- • Data contracts & ownership
- • Lineage & impact analysis
- • Feature store readiness
Data Repair & Quality Monitor
Continuous detection, alerting and automated repair of data quality issues across your pipelines — so bad data never reaches AI or reporting.
- • Automated anomaly & drift detection
- • Rule-based + ML quality checks
- • Self-healing repair workflows
- • Real-time quality dashboards & SLAs
Zero-Downtime Legacy Migrations
Surgical moves from long-running on-premise systems to modern lakehouses. We build automated reconciliation engines and idempotent cutovers so the business keeps running.
How we work
Short, focused engagements with clear outcomes. No endless retainers.
Discover
Understand your current architecture, pain points, and the business outcomes that matter.
Diagnose
Map failure modes, cost drivers and metadata gaps. Deliver a prioritised, actionable plan.
Build
Implement robust pipelines and metadata foundations with production observability from day one.
Hand over
Document everything, upskill your team, and leave you with systems you can own and extend.
Selected Work
Hard engineering outcomes for New Zealand enterprises. Zero anonymized filler.
Mass-Scale Reconciliation for Risk & Audit
Architected massive-scale automated data reconciliation frameworks covering thousands of tables. Delivered absolute data fidelity for national risk and audit management.
Zero-Downtime Legacy CRM Migration
Re-engineered 30-year legacy account-centric models into scalable relational structures. Built validation frameworks guaranteeing 100% data parity and zero loss during production cutover.
Forensic Data Remediation & Integrity
Engineered automated reconciliation processes to clean up historical base-data inaccuracies and resolve high-stakes data integrity incidents within complex legacy datasets.
Self-Maintaining Enterprise Data Warehouse
Architected automated ETL frameworks processing thousands of tables across disparate systems, eliminating manual spreadsheets and establishing reliable data governance.
Built for New Zealand conditions
HPDL is a specialist data engineering practice focused on the hard problems generalist consultancies often leave unfinished: reliable, observable, AI-ready data logistics.
We work with mid-market and larger New Zealand organisations that have already invested in Databricks, Snowflake or Azure Fabric — and now need those platforms to deliver under real operational pressure.
Small team. High ownership. Direct access to senior engineers who have shipped production systems at scale.
Ready to stop firefighting pipelines?
Book a free 30-minute call. We’ll look at your current architecture and whether a focused engagement makes sense.
Book a 30-min Call →Prefer to send a note first?
Or email: info@hpdl.co.nz