Data Engineer

We’re powered by purpose

Mable is an online platform connecting Australians looking for disability and aged care support to independent support workers. Since 2014, we’ve been helping our community live their kind of independence, and today we’re one of Australia's largest and fastest growing healthtech platforms. 

We  have been recognised in AFR’s Fast 100 list, Deloitte’s Tech Fast 50, and won the Australian Growth & Australian Technology Growth Company of the Year Award in 2020! So don’t miss  your  opportunity to join a thriving scale-up and deliver change to  Australia’s care and support sector.

As a Data Engineer - at Mable you will collaborate with Business System and Product Engineering teams to understand changes to existing data structures as well as new data sources. You will then ingest, transform and structure data following data warehousing best practices in order to maintain an accurate, scalable and consumable source of truth in our Data Lakehouse, Databricks. You will be at the heart of a fast-paced, high growth environment where you will help drive real-world impact.

As a Data Engineer at Mable, your contribution to ensuring we have a single accurate, well structured source of truth is fundamental to enabling our Data Analysts and Scientists to build reporting, machine learning models and extract actionable insights from data to drive strategic business decisions.

What will I be doing?

• Work collaboratively with our Business system and Product engineering teams to understand upcoming changes to their systems, and flow on impact to our data models in Databricks.
• Work collaboratively with our broader Data Science & Analytics team to understand their data needs.
• Build, enhance and monitor data ingestion from both internal and external sources.
• Cleanse, transform and model data; combining datasets from multiple systems for downstream consumption and visualisation.
• Data governance, including both enriching the metadata of our data assets, data quality and data access.

What are we looking for?

• 1-2 years of Data Engineering/Warehousing/Modelling experience working in an agile environment.
• Experience using SQL to clean, transform and build data models for use by Data Analysts and Data Scientists.
• Verbal and written communication skills with technical stakeholders.
• Experience developing, deploying and monitoring cloud based data ingestion solutions.
• Understanding of Data Modelling concepts including Dimensional Modelling and Slow Changing Dimensions.
• Comfort with ambiguity, a fast-paced environment, and rapid business growth.

What else would make a difference?

• Advanced education in a relevant field such as computer science, information technology or analytics
• Experience working with Databricks and AWS
• Experience in Python; in particular PySpark and Spark Streaming
• Experience using GIT and understanding of CICD concepts