May 24, 2023
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Melbourne, Victoria, Australia, Australia
May 24, 2023
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Data Engineer– Wholesale Credit & Corporate Finance
Design, build, test and maintain the AWS data architecture and supporting services.
Work with a driven, dynamic, supportive team.
As a Data Engineer, you will work on large-scale data management concerns in a dynamic and complex environment. In this role, you will provide your expertise in designing, implementing, and executing a robust, scalable, and cost-effective shared-services data platform. You will have an appreciation, understanding and working knowledge of modern data architecture paradigms (Data Mesh).
The role will also support innovation by monitoring emerging technologies/methods and championing those that will add value.
This role supports a divisional data mesh and all data and analytics use cases for Institutional.
It reports to the Data Engineer Lead for IDAP.
Who are you?
A data enthusiast and technologist – you have a good understanding of data, the underlying technology and the architecture that supports it. You are versatile and have a fast learning rate.
A problem solver – you are energised by tackling complex problems and using critical thinking, your network, skills, knowledge, and data to drive better outcomes for our customers and the bank
The customer’s biggest fan – you demonstrate a thirst for a better understanding of ANZ’s customers and seeing problems and solutions through their eyes.
Continuous improvement junkie – you constructively challenge the status quo, look for better ways to do things and passionately advocate continuous improvement.
Comfortable being uncomfortable – you are comfortable with uncertainty and can effectively manage yourself through ambiguity and change.
Risk savvy – you build sustainable solutions that protect customers, stakeholders, and the community.
A team player – you recognise and value the different perspectives and skills your colleagues bring.
Committed to your own growth and that of others – you challenge and improve yourself and others by identifying your development areas, seeking feedback, and providing feedback to others
What you bring to the WCCF Tech Area
Good understanding and experience working with big data and associated concerns (data governance, scalability, security, observability, reliability, etc).
Experience in designing and building data pipelines using AWS technologies like Lake Formation, MWAA, EMR, S3, and Athena.
Experience with data warehousing technologies (AWS Redshift) and data storage formats (Parquet, Avro, JSON) and table formats (governed tables, Iceberg).
Experience with data transformation and testing tools and frameworks (dbt, Great Expectations, Soda)
4+ years of industry experience in data and/or software engineering, data science, business intelligence, or related fields.
Good proficiency in programming (Python, Rust, GoLang or Java, with strong SQL knowledge).
Relevant AWS Cloud Certifications.
Preferable - Data modelling experience to support business requirements for data usage.
Comfortable with IaC and CI/CD tools (Terraform, Codefresh)
Experience developing data visualisations using tools such as Tableau, Qlik, or similar.
Proven skill in communicating and collaborating with analysts and engineers within the team.
What Will Your Day Look Like
Collaborating with the Lead Data Engineer and/or Data Architect to understand the demands on the data platform, elaborating on these to produce solution options.
Work with domain and data platform teams to analyse data sets, and design and build data pipelines.
Analyse and organise raw data from domains, including combining and aggregating raw data from various internal and external sources.
Building models to transform data to suit the data querying needs of consumers.
Collaborating with data and cloud engineers to develop solution options, and maintaining key design artefacts, e.g., Solution Design overview.
Building relationships with key business and technology stakeholders, providing technical input and support in their quest to contribute towards an Institutional and enterprise data mesh.
Supporting the evaluation of new technologies to support capability gaps and performance improvements.
Location, Sydney, Melbourne
Req 2 Lead Data Engineer– Wholesale Credit & Corporate Finance
Lead Data Engineer– Wholesale Credit & Corporate Finance
Help set the technical direction for the Institutional Data and Analytics Platform.
Collaborate with data domain teams to understand their needs for a shared-services data platform.
Define, design, build, test and maintain the AWS data architecture and supporting services.
Work with a driven, dynamic, supportive team.
As a Lead Data Engineer, you will work on large-scale data management concerns in a dynamic and complex environment. In this role, you will design, build, test, deploy and maintain a highly scalable, resilient, cost-effective, and recoverable data management platform using a software engineering mindset and applying the principles of DataOps. You will be responsible for leading a team of engineers, and working closely with the platform Product Owner, architects and another senior stakeholder to engineer a modern data platform.
You will have an appreciation, understanding and working knowledge of modern data architecture paradigms (Data Mesh).
The role will also support innovation by monitoring emerging technologies/methods and championing those that will add value.
This role supports a divisional data mesh, and all data and analytics use cases for Institutional.
It reports to the XXXX for WCCF.
Who are you?
A data enthusiast and technologist – you have a broad and deep understanding of data, the underlying technology and the architecture that supports it. You are versatile and have a fast learning rate.
A problem solver – you are energised by tackling complex problems and using critical thinking, your network, skills, knowledge, and data to drive better outcomes for our customers and the bank.
The customer’s biggest fan – you demonstrate a thirst for better understanding ANZ’s customers and seeing problems and solutions through their eyes.
Continuous improvement junkie – you constructively challenge the status quo, look for better ways to do things and passionately advocate continuous improvement.
Comfortable being uncomfortable – you are comfortable with uncertainty and can effectively manage yourself through ambiguity and change.
Risk savvy – you build sustainable solutions that protect customers, stakeholders, and the community.
A team player – you recognise and value the different perspectives and skills your colleagues bring.
Committed to your own growth and that of others – you challenge and improve yourself and others by identifying your own development areas, seeking feedback, and providing feedback to others.
What you bring to the WCCF Tech Area
Solid understanding and working with big data and associated concerns (data governance, scalability, security, observability, reliability, etc.).
Proven experience with integrating multiple heterogeneous data sources, and building a robust, cost-effective, flexible, and large-scale data and analytics platform.
Deep experience in building large-scale data management and processing platforms, using AWS technologies like Lake Formation, MWAA, EMR, S3, and Athena.
Experience with data warehousing technologies (AWS Redshift) and data storage formats (Parquet, Avro, JSON) and table formats (governed tables, Iceberg).
Experience with data transformation and testing tools and frameworks (dbt, Great Expectations, Soda)
8+ years of industry experience in data and/or software engineering, data science, business intelligence, or related fields.
Strong proficiency in programming (Python, Rust, GoLang or Java, with advanced SQL knowledge).
Tertiary qualification with a focus on software development, and the relevant AWS Cloud Certifications (Data speciality preferred).
Data modelling experience to support business requirements for data usage.
Good working experience with IaC and CI/CD tools (Terraform, Codefresh)
Experience developing data visualisations using tools such as Tableau, Qlik, or similar.
Successful track record in managing or leading a team of data engineers.
Proven skill in consulting, communicating, and influencing.
What Will Your Day Look Like
Collaborating with business and technology stakeholders to understand their domain and demands on the data platform, elaborating on these together with the data architect to produce solution options.
Collaborating with data and cloud engineers to develop solution options, and maintaining key design artefacts, e.g., Solution Design overview.
Presenting key design artefacts with the architect to the appropriate governance forums.
Collaborating with other architects, analysts, engineers, and subject matter experts to ensure that the established design guidelines and patterns are clearly communicated and understood. Also ensuring projects align with it.
Building relationships with key business and technology stakeholders, providing technical guidance and support in their quest to contribute towards an Institutional and enterprise data mesh.
Supporting the evaluation of new technologies to support capability gaps, and performance improvements.
Mentor junior team members, and teams across the divisional-wide data mesh.
Design, build, test and maintain the AWS data architecture and supporting services.
Work with a driven, dynamic, supportive team.
- Role Location: Melbourne or Sydney
As a Data Engineer, you will work on large-scale data management concerns in a dynamic and complex environment. In this role, you will provide your expertise in designing, implementing, and executing a robust, scalable, and cost-effective shared-services data platform. You will have an appreciation, understanding and working knowledge of modern data architecture paradigms (Data Mesh).
The role will also support innovation by monitoring emerging technologies/methods and championing those that will add value.
This role supports a divisional data mesh and all data and analytics use cases for Institutional.
It reports to the Data Engineer Lead for IDAP.
Who are you?
A data enthusiast and technologist – you have a good understanding of data, the underlying technology and the architecture that supports it. You are versatile and have a fast learning rate.
A problem solver – you are energised by tackling complex problems and using critical thinking, your network, skills, knowledge, and data to drive better outcomes for our customers and the bank
The customer’s biggest fan – you demonstrate a thirst for a better understanding of ANZ’s customers and seeing problems and solutions through their eyes.
Continuous improvement junkie – you constructively challenge the status quo, look for better ways to do things and passionately advocate continuous improvement.
Comfortable being uncomfortable – you are comfortable with uncertainty and can effectively manage yourself through ambiguity and change.
Risk savvy – you build sustainable solutions that protect customers, stakeholders, and the community.
A team player – you recognise and value the different perspectives and skills your colleagues bring.
Committed to your own growth and that of others – you challenge and improve yourself and others by identifying your development areas, seeking feedback, and providing feedback to others
What you bring to the WCCF Tech Area
Good understanding and experience working with big data and associated concerns (data governance, scalability, security, observability, reliability, etc).
Experience in designing and building data pipelines using AWS technologies like Lake Formation, MWAA, EMR, S3, and Athena.
Experience with data warehousing technologies (AWS Redshift) and data storage formats (Parquet, Avro, JSON) and table formats (governed tables, Iceberg).
Experience with data transformation and testing tools and frameworks (dbt, Great Expectations, Soda)
4+ years of industry experience in data and/or software engineering, data science, business intelligence, or related fields.
Good proficiency in programming (Python, Rust, GoLang or Java, with strong SQL knowledge).
Relevant AWS Cloud Certifications.
Preferable - Data modelling experience to support business requirements for data usage.
Comfortable with IaC and CI/CD tools (Terraform, Codefresh)
Experience developing data visualisations using tools such as Tableau, Qlik, or similar.
Proven skill in communicating and collaborating with analysts and engineers within the team.
What Will Your Day Look Like
Collaborating with the Lead Data Engineer and/or Data Architect to understand the demands on the data platform, elaborating on these to produce solution options.
Work with domain and data platform teams to analyse data sets, and design and build data pipelines.
Analyse and organise raw data from domains, including combining and aggregating raw data from various internal and external sources.
Building models to transform data to suit the data querying needs of consumers.
Collaborating with data and cloud engineers to develop solution options, and maintaining key design artefacts, e.g., Solution Design overview.
Building relationships with key business and technology stakeholders, providing technical input and support in their quest to contribute towards an Institutional and enterprise data mesh.
Supporting the evaluation of new technologies to support capability gaps and performance improvements.
Location, Sydney, Melbourne
Req 2 Lead Data Engineer– Wholesale Credit & Corporate Finance
Lead Data Engineer– Wholesale Credit & Corporate Finance
Help set the technical direction for the Institutional Data and Analytics Platform.
Collaborate with data domain teams to understand their needs for a shared-services data platform.
Define, design, build, test and maintain the AWS data architecture and supporting services.
Work with a driven, dynamic, supportive team.
- Role Location: Melbourne
As a Lead Data Engineer, you will work on large-scale data management concerns in a dynamic and complex environment. In this role, you will design, build, test, deploy and maintain a highly scalable, resilient, cost-effective, and recoverable data management platform using a software engineering mindset and applying the principles of DataOps. You will be responsible for leading a team of engineers, and working closely with the platform Product Owner, architects and another senior stakeholder to engineer a modern data platform.
You will have an appreciation, understanding and working knowledge of modern data architecture paradigms (Data Mesh).
The role will also support innovation by monitoring emerging technologies/methods and championing those that will add value.
This role supports a divisional data mesh, and all data and analytics use cases for Institutional.
It reports to the XXXX for WCCF.
Who are you?
A data enthusiast and technologist – you have a broad and deep understanding of data, the underlying technology and the architecture that supports it. You are versatile and have a fast learning rate.
A problem solver – you are energised by tackling complex problems and using critical thinking, your network, skills, knowledge, and data to drive better outcomes for our customers and the bank.
The customer’s biggest fan – you demonstrate a thirst for better understanding ANZ’s customers and seeing problems and solutions through their eyes.
Continuous improvement junkie – you constructively challenge the status quo, look for better ways to do things and passionately advocate continuous improvement.
Comfortable being uncomfortable – you are comfortable with uncertainty and can effectively manage yourself through ambiguity and change.
Risk savvy – you build sustainable solutions that protect customers, stakeholders, and the community.
A team player – you recognise and value the different perspectives and skills your colleagues bring.
Committed to your own growth and that of others – you challenge and improve yourself and others by identifying your own development areas, seeking feedback, and providing feedback to others.
What you bring to the WCCF Tech Area
Solid understanding and working with big data and associated concerns (data governance, scalability, security, observability, reliability, etc.).
Proven experience with integrating multiple heterogeneous data sources, and building a robust, cost-effective, flexible, and large-scale data and analytics platform.
Deep experience in building large-scale data management and processing platforms, using AWS technologies like Lake Formation, MWAA, EMR, S3, and Athena.
Experience with data warehousing technologies (AWS Redshift) and data storage formats (Parquet, Avro, JSON) and table formats (governed tables, Iceberg).
Experience with data transformation and testing tools and frameworks (dbt, Great Expectations, Soda)
8+ years of industry experience in data and/or software engineering, data science, business intelligence, or related fields.
Strong proficiency in programming (Python, Rust, GoLang or Java, with advanced SQL knowledge).
Tertiary qualification with a focus on software development, and the relevant AWS Cloud Certifications (Data speciality preferred).
Data modelling experience to support business requirements for data usage.
Good working experience with IaC and CI/CD tools (Terraform, Codefresh)
Experience developing data visualisations using tools such as Tableau, Qlik, or similar.
Successful track record in managing or leading a team of data engineers.
Proven skill in consulting, communicating, and influencing.
What Will Your Day Look Like
Collaborating with business and technology stakeholders to understand their domain and demands on the data platform, elaborating on these together with the data architect to produce solution options.
Collaborating with data and cloud engineers to develop solution options, and maintaining key design artefacts, e.g., Solution Design overview.
Presenting key design artefacts with the architect to the appropriate governance forums.
Collaborating with other architects, analysts, engineers, and subject matter experts to ensure that the established design guidelines and patterns are clearly communicated and understood. Also ensuring projects align with it.
Building relationships with key business and technology stakeholders, providing technical guidance and support in their quest to contribute towards an Institutional and enterprise data mesh.
Supporting the evaluation of new technologies to support capability gaps, and performance improvements.
Mentor junior team members, and teams across the divisional-wide data mesh.
