Mid/Senior Data Analytics Engineer (HCL x ANZ Bank)

What will your day look like: Understand user stories supporting a wide array of use cases such as reporting in Tableau, data science or analytics activities, or indeed operational data flows for decisioning and campaign tools  Design physical data structures in Google Big Query to optimise efficiency, scalability and consistency in a repeatable manner  Catalogue and document metadata on available data sources and communicate rationale for modelling decisions made  Work closely with the team to ensure data models align with stakeholder expectations and practical engineering patterns in DBT and Terraform  Profile incoming source data (batch and real-time event) to deeply understand data, contribute to data integration specifications and help to build robust and future-proof models  Participate in the continuous improvement of data assets and governance processes to enable customers to easily access the data they need  What will you bring?To grow and be successful in this role, you will ideally bring the following: From 4 years experience Excellent English communication skills  Excellent SQL, data analysis and data profiling skills  Proven success designing and/or building BI/DW or ETL solutions, especially using data transformation tools such as DBT or Dataform  Demonstrated experience with data pipeline orchestration and/or configuration as code  Exposure to data in cloud-native environments  An appreciation for difficult problems and to work autonomously on complex tasks  The Analytics Engineer role is a midpoint between Data Analyst and Data Engineer; you need to ‘care’ about the data itself, not just the pipelines, but also be comfortable with engineering practices such as source control, tagging, CI/CD and automated testing using Python.  At ANZ a growth mindset is at the heart of our culture and we actively encourage people to try new things. If this role interests you and you feel you have most of these things in your toolbox, we’d love to hear from you.