Production-grade Snowflake platform delivered on AWS
A full DataOps lifecycle
And a live working customer facing use case
On demand ingestion, event driven refresh, and governed external API access built to proper standards from day one, not retrofitted later.
Automated data refresh, consumer auto-provisioning, consumption monitoring, and account level cost controls.
Headway Systems is one of New Zealand’s leading providers of property and sales data for property professionals and the only locally owned and operated bulk property data supplier in the country. With over 20 years of industry experience and 50% ownership held by the New Zealand Institute of Valuers (NZIV), Headway manages and integrates Territorial Authority and Land Information NZ data nationwide and distributes property and valuation data to valuation practices, and other property data users across New Zealand.
With the launch of its new API platform, Headway is expanding beyond traditional data delivery models to provide secure, on-demand, programmatic access to enriched property data, positioning the company to serve emerging proptech and analytics-driven markets.
Headway’s data operations relied on legacy systems that had become difficult to maintain and slow to adapt. Ingestion was entirely manual: staff extracted, cleaned, and merged data outside the platform before uploading into Snowflake via the UI. There was no direct connection between source systems and Snowflake, no automation, and no mechanism to keep downstream datasets current without ongoing human effort.
Integrating new data sources was difficult within the existing setup. And with an externally facing use case on the roadmap, the solution would need to meet a higher bar for security and governance from the start.
The objective was to modernise on Snowflake: establish on-demand ingestion to reduce operational cost, implement proper environments and DataOps practices, and deliver a production-ready, customer-facing use case without the shortcuts that create technical debt and force a rebuild later.
Headway partnered with dataengine to design and deliver a modern, scalable Snowflake data platform on AWS, built not just to solve current challenges but to enable future product innovation.
The approach prioritised a strong platform foundation first, ensuring speed of delivery without compromising long-term scalability or governance.
As a Snowflake and AWS partner, dataengine took a platform-first approach. Rather than building directly to the use case, the team established the full platform foundation first, covering dev, test, and production environments, a DataOps lifecycle, and a medallion architecture, then layered the use case on top. This sequencing is what made it possible to move at speed without compromising on standards.
Platform Foundation
The platform was built on Snowflake with proper environment separation (dev, test, prod) and a full DataOps lifecycle from day one. Data is structured using a medallion architecture: raw source files land in a Bronze layer for full traceability, and a transformation pipeline produces consumer-ready Gold layer datasets. Automated ingestion pulls data from Headway’s SFTP server using a Python-based Snowpark procedure, with credentials managed through Snowflake Secrets and network access controlled via a dedicated External Access Integration.
Automated Refresh
Refresh of Gold layer datasets is fully event-driven. Snowflake streams on each Bronze table detect new data and automatically trigger a refresh, with no scheduled polling and no manual steps required. When new data arrives, it flows through to consumer-ready datasets without any intervention.
Intelligent Matching
The consumer-facing function includes intelligent matching logic that returns confidence-graded results, allowing consumers to act on data with clarity rather than having to interpret ambiguous records themselves.
Governed External Access
External consumers access data exclusively through a controlled Snowflake function, with no direct table access at any level. Consumer provisioning is automated end-to-end via a single stored procedure covering role creation, user configuration, schema cloning, and Programmatic Access Token (PAT) generation. Offboarding is handled with equal simplicity and no data loss.
Because the use case is customer-facing, security and governance were treated as first-class requirements, not afterthoughts. Role-based access control, controlled interfaces, and audit-ready logging are built into the platform architecture.
Monitoring and Cost Controls
Every API call is logged with user identity, query volume, and response time, surfaced through a real-time Snowsight dashboard for consumer visibility. An account-level resource monitor with automated notification and suspension thresholds ensures cost exposure is bounded as usage scales, giving Headway operational confidence from day one.
In just three weeks, Headway successfully launched a production-ready data platform and its first customer-facing API use case. Delivered in partnership with dataengine, the solution combines speed with strong architectural foundations, avoiding technical debt while enabling long-term scalability.
Key outcomes include:
This collaborative success demonstrates the value of combining:
Headway’s deep domain expertise in property data with dataengine’s modern data engineering capability.
Ready to modernise your data platform or launch new data products? Talk to Headway Systems or dataengine.
