At ANZ, everything we do boils down to 'why' – our purpose – to shape a world where people and communities thrive. We're just as focused on seeing our people thrive as well as our customers. We'll give you every opportunity to develop your career. We are responding faster to changing customer requirements, focusing on the things that matter the most, energising our people, eliminating waste and reducing bureaucracy.
ANZ has started to move to a new way of working, leveraging agile practices. To understand more about this new way of working and if this role is right for you, we strongly encourage you to take a look at The ANZ Way vimeo channel where you'll find 'The ANZ Way' animation and the 'New Ways of Working' animation.
We've also got some great information about what it's like to work in 'Data@ANZ' on our new LinkedIn Life page .
And now the role:
Our teams are hungry to gain and act on insights from our large online and offline datasets, but our two most important data sources aren't linked together in the way we need. So, we're looking for a motivated data engineer who's keen to hit the ground running and help us integrate these data sources, enabling us to build an end-to-end view of customer behaviour, interventions and outcomes, so that we can attribute success (or failure) to different parts of the online (and offline) customer journey, and take action.
Working closely with our Digital Analytics CoE, you'll be able to influence the data we collect in digital channels, enhance our personalisation capability through increased breadth and depth of data, and see tangible business outcomes driven from your work – an opportunity that many data engineers don't get to see up close.
This role sits within our Digital Sales Experience Tribe, where the mission is to attract and engage customers to evaluate, acquire and activate solutions that meet their banking needs, and to grow digital sales while improving customer experience.
What will be in your toolkit?
You will have excellent interpersonal skills and the ability to build strong stakeholder relationships both internally and externally
You will have proven leadership skills and experience
3 years' experience working as a Data Engineer in building data pipelines, familiar with ETL patterns and frameworks, tools and technologies and their use in business contexts
Good SQL and scripting skills will be necessary for this position, as well as good database knowledge and modelling experience (SQL & NoSQL)
Demonstrated ability to write scripts and procedures which perform ETL on platforms such as Teradata and Oracle, integrating large disparate data sources into conformed and derived data assets to support ad-hoc analytics, reporting, modelling, and attribution
Interest in solving the challenge of taking online and offline behavioural datasets and combining them to understand cause and effect, attribute outcomes to interventions, and inform day-to-day and strategic business decisions
Depending on the specific role, a mix of
Technical experience with programming in Python, R (C , Java and Akka) and statistical packages (R, SAS)
Data Governance, Quality & Control skills and experience
Continuous Integration/deployment when building data pipelines
Process automation, deep system expertise, forensic mindset in banking system is a plus
Ability to effectively communicate to all stakeholders (technical and non-technical); Without this all the work is meaningless
Experience in reporting/BI tools such as Qliksense or Qlikview
What might a day in the life look like?
Address and solve complex cross business issues using large amounts of data across multiple technologies and data platform capabilities
Advocate for the data engineering profession as part of the full data & analytics delivery capability
Be accountable for the data architecture and patterns related to solving data, reporting, analytics, decisions and campaigns for Australia Retail & Commercial Division
Develop scalable advanced data models including the preparation and reconciliation of data and creation of interactive visualisations
Initiate, design and implement innovative trends in the field of data engineering and data science
Implement batch and streaming data pipelines processes and patterns to integrate with existing and new data sources and target applications
Uplift governance and quality of data and analytical models, standards and controls
Uplift continuous deployment and integration/test automation capabilities to increase speed to market, quality and robustness of new data assets/models/insights
Run knowledge sharing and/or skills uplift sessions with the broader analytical community through chapter-of-chapter meetups
Engineer/ prototype / industrialise scalable data assets and platforms needed for analytics
At ANZ we aim to create an inclusive environment where employee differences such as gender, age, culture, disability, sexual orientation, family and caring responsibilities and religion are valued and supported. We work flexibly at ANZ. Talk to us and let us know how this role can be flexible for you. #GD4.3
Internal Number: 6468016
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