Founded in Australia in 1945, CHEP is a leading provider of pallet and container pooling services for the Aerospace, Automotive, Chemical, Consumer Goods, Fresh Food and Manufacturing industries.
CHEP provides equipment pooling which is the shared use of high quality standard pallets and containers by multiple customers.
Pooling is a strateg...
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Create and maintain optimal data pipeline architecture,
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
Build analytics tools that utilise the data pipeline to provide actionable insights into operational efficiency and other key business performance metrics.
Work with stakeholder teams to assist with data-related technical issues and support their data infrastructure needs.
Keep our data separated, documented and secure through the development of a centralised analytics data lake for the APAC region.
Create data tools for analytics and data scientist team members that assist them in building and optimising our data product into being an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems.
Use large datasets to build dashboards and reports to support senior management in effective decision making.
Design effective reports and dashboards using visualisation techniques and tools
What will ensure your success in the Role:
Educational Background: Relevant tertiary qualifications in Computer Science, Statistics, or related technical fields.
Extensive Experience: +7 years of experience in similar position preferable in complex environments in multinational companies
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Data modelling in SQL Server Analysis Services & Power BI plus experience using other visualisation tools
Experience building and optimizing ‘big data’ data pipelines (distributed processing systems), architectures and data sets. Preferably Apache Spark
Building reports and dashboards – ideally in Power BI Desktop or other visual tools
Experience with cloud solutions in Azure/AWS
Familiar with SCRUM / Agile working methods
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Build processes supporting data transformation, data structures, metadata, dependency and workload management.
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