At ANZ our purpose is to shape a world where people and communities thrive. We’re making this happen by improving our customers’ financial wellbeing so they can achieve incredible things – be it buying their home, building a business or saving for things big or small.

Our purpose in the Marketing Analytics Tribe is to enable the Personalisation and Digital Sales Experience tribes with their data science, data engineering and analytics needs, along with servicing the wider enterprise.

As a Data Engineer - Infrastructure in Marketing Analytics, you will be working with other data engineers and data scientists on a new (to ANZ) cloud-ready platform to enable and optimise machine learning models and analytic workflows. Your experience in building and optimising infrastructure for data science will be essential to help Marketing Analytics uplift their data engineering and data science capability.

What Will Your Day Look Like

• Liaise with data scientists, data analysts to understand requirements
• Support data engineers by understanding their requirements for ETLs and data management and how to enable them
• Work collaboratively with stakeholders within and outside of your squad to enable teams, pipelines and workloads and provide guidance to optimise workloads.
• Support data scientists by optimising the platform to ensure optimal model performance
• Work with the data capability team to understand the roadmap and help to uplift the platform in line with Marketing Analytics tribe needs
• Optimise data flows by building robust, fault-tolerant data pipeline that cleans, transforms, and aggregates unorganized and messy data
• Promote a culture within the Tribe and the Chapter, encouraging best practices around reviews, quality and documentation
• Consult with data engineers on the optimal data structures for data ingestion, integration and analytics layers on a variety of technologies
• Contribute to strategy and roadmap for Marketing Analytics to support personalisation
  
  
  

What will you bring?

We know not everyone will bring all of the skills and experience, and at ANZ we are focused on people bringing a growth mindset to their approach to work. Some of the skills we are looking for are below, but don’t worry if you don’t have all of these as learning on the job is the way we work. So if this role interests you and you feel you have most of these things in your toolbox, we’d love to hear from you. But back to some of the skills –

• Have an outcome focused mindset
• You have some experience in managing infrastructure in cloud environments (AWS/GCP/Azure)
• Hands-on knowledge and experience on ETL, automated data pipelines and ML models
• You have used CI/CD pipelines (git, github, bitbucket or similar) and understand how they work and you understand what automation testing is and how to implement it
• You have experience with Airflow and/or dbt
• You know how distributed systems can fail
• Experienced with common design and architectural patterns coupled with a passion for writing clean code that is performant and well tested.
• You understand the difference between a “data product” and a “data asset”
• Excellent communication skills and the ability to articulate complex, technical concepts to non-technical audiences.
• Software Engineering experience with proficiency in at least one high-level programming language (Python, Java)
• Hands-on knowledge and experience with tools and techniques for data manipulation and analysis (e.g. SQL)
• Experience with in at least one high-volume data processing environment (Teradata, Oracle, Cloudera, BigQuery or equivalent)
• Understanding of big data architectures (data) and communication protocol and scheduling, data management, performance tuning, including cloud scalability.
• Experience working with of Jira, Confluence or similar
• Ability to work independently whilst also being a good team player.