In today’s data-driven world, organisations rely on
accurate and timely workforce information to make
informed decisions. However, integrating HR and payroll
data from cloud-based platforms like Employment Hero can
present significant technical challenges especially when
dealing with complex APIs, short-lived tokens, and large
data volumes.
At DATA LEAGUE, we recently helped a client overcome
these challenges by developing a metadata-driven data
integration framework that connects seamlessly with the
Employment Hero API and ingests data into a modern
medallion data architecture. The result? Faster,
automated, and more reliable access to insights in days
instead of weeks.
The Challenge: Short Token Expiry and Complex Data
Pipelines
Employment Hero’s APIs provide rich HR, payroll, and
employee data but the access tokens used to authenticate
API calls expire every 15 minutes. This short lifespan
can interrupt long-running data ingestion processes,
causing failures and manual restarts if not properly
managed.
Additionally, the client needed to integrate multiple
API endpoints and load data efficiently into their data
warehouse, all while maintaining scalability,
reusability, and cost efficiency.
Our Solution: Metadata-Driven Integration Framework
To address these challenges, our data engineers designed
a metadata-driven framework built on modern cloud
technologies (e.g., Azure Data Factory, Azure Key Vault,
Azure Logic App and Azure SQL).
This approach allows data ingestion and transformation
pipelines to be configured dynamically based on metadata
eliminating the need for repetitive pipeline
development.
