Data Engineer

at  endeavour group

LET’S CREATE A MORE SOCIABLE FUTURE TOGETHER

At Endeavour, we’re totally into what we do. With a portfolio that includes Dan Murphy’s, BWS, ALH Hotels, Pinnacle Drinks and more, we love to bring people together. Together we share our passion for our products and industry; it’s what inspires us to dream big, and continue to create new experiences for our customers and teams across Australia. If you thrive on positive energy, we want to meet you!
Job Description
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Be uniquely you, come as you are
You’re customer focused and passionate about being part of a tribe of great people and you actively contribute to your workplace community.
With a growth mindset, you orient around doing what’s meaningful, purposeful and delivers value. You’re excited about being part of a data-led transformation at one of Australia’s biggest companies.
You’re curious and empathetic. You have an eye for the bigger picture while also ensuring the details are in order. You deal with complexity by collaborating with colleagues, listening to customers, testing ideas and continuously learning. You take authorship for what you create.
Our Chapter combines Data Engineering concepts to deliver data centric systems, products and applications.
Sound good? Read on.

Here is a taster of what you can expect in this role:

• Analysis
• Work with squad members and business SMEs to understand the requirements including business problem or opportunity, data feed/pipeline requirements, model design, features and/or reporting requirements
• Contribute to documentation of requirements and user stories in Jira/Confluence, as required
• Delivery
• Design, Build and deploy data pipelines required for the relevant initiative - could be to support analytics, reporting, machine learning, data migration and/or data archiving requirements
• Document relevant information required for knowledge sharing across the team and for operational support handover
• Knowledge sharing amongst the data engineering chapter and squad team members
• Collaborate with team and stakeholders to ensure successful delivery
• Contribute and adhere to technology standards, data governance & privacy policies and IT security standards
• Adhere to corporate governance policies and architecture best practice
• Attend/contribute to squad agile ceremonies (e.g. standups, sprint planning etc)
• Where required, support ML Engineers to implement and deploy scalable ML models and features (as designed by data scientists), adhering to enterprise CI/CD and devops practices
• Where required, support ML Engineers to optimise execution performance (time and cost) of models
• Where required, support integration, orchestration and visualisation components.
• Operations
• Contribute and assist with handover documentation to by used by operations team for new builds/enhancements
• 3rd level support for incidents relating to productionised data pipelines, Tableau and/or ML models
• Comply with the change process and provide inputs, as required, and attend CAB, where required

Qualifications

Now let’s talk about you:

• Must Have
• Cloud data pipeline build, deploy and maintain/support skills
• Python, DBT, Airflow and SQL skills
• Experience with distributed programming (e.g. Apache Spark)
• An in-depth understanding of common databases and data structures.
• Back-end development skills, such as APIs
• Experience working with big data cloud platforms (Azure, Google Cloud Platform, AWS)
• Experience working in agile environment
• DevOps and CI/CD
• Google Cloud Platform experience (Composer, Cloud Run, Cloud Functions, GCS, BigQuery, etc.)
• Experience working with Personally Identifiable Information (PII) data
• Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes, Airflow).
• Skills in designing and executing tests to ensure data quality, including validation of completeness, correctness, consistency, accuracy, and timeliness of data.
• Experience with conceptual, logical, physical and dimensional data modelling.
• Desired
• Databricks experience
• Tableau administration experience
• Experience working with retail offline (e.g. store sales) and online data sets (e.g. ecommerce)
• Experience working with unstructured data
• Data science knowledge
• Retail industry experience
• Software engineering experience/skills
• Experience with Infrastructure as code
• Experience with Java and/or C#
• Experience with Object-Oriented programming (OOP)
• Experience with Unit Testing, TDD

• Analysis
• Work with squad members and business SMEs to understand the requirements including business problem or opportunity, data feed/pipeline requirements, model design, features and/or reporting requirements
• Contribute to documentation of requirements and user stories in Jira/Confluence, as required
• Delivery
• Design, Build and deploy data pipelines required for the relevant initiative - could be to support analytics, reporting, machine learning, data migration and/or data archiving requirements
• Document relevant information required for knowledge sharing across the team and for operational support handover
• Knowledge sharing amongst the data engineering chapter and squad team members
• Collaborate with team and stakeholders to ensure successful delivery
• Contribute and adhere to technology standards, data governance & privacy policies and IT security standards
• Adhere to corporate governance policies and architecture best practice
• Attend/contribute to squad agile ceremonies (e.g. standups, sprint planning etc)
• Where required, support ML Engineers to implement and deploy scalable ML models and features (as designed by data scientists), adhering to enterprise CI/CD and devops practices
• Where required, support ML Engineers to optimise execution performance (time and cost) of models
• Where required, support integration, orchestration and visualisation components.
• Operations
• Contribute and assist with handover documentation to by used by operations team for new builds/enhancements
• 3rd level support for incidents relating to productionised data pipelines, Tableau and/or ML models
• Comply with the change process and provide inputs, as required, and attend CAB, where require