Cloud Data Engineer – Banking Platform (6-Month Contract)

Whizdom; Sydney; On-site; AUD 112,000 - 179,000; Full time

Job summary

Whizdom is partnering with a leading consulting organisation to hire an experienced Context Engineer for a major banking program in Australia. This hands-on role focuses on building scalable cloud data solutions, data integration and governance across cloud and on-prem environments.

You will design, develop and optimise batch and near real-time data pipelines using Snowflake, Python, Spark, and Azure Data Factory, collaborating with stakeholders to deliver enterprise-scale data platforms with

Qualifications

• Design, build and support enterprise data solutions across cloud and on-prem environments.
• Deliver batch and near real-time pipelines, data integration, modelling and governance.
• Implement data quality, governance and security controls.

Responsibilities

• Design and develop scalable data pipelines and integration solutions.
• Build ETL/ELT processes using modern cloud technologies.
• Develop and maintain data models, mappings and documentation.
• Implement data quality, governance and security controls.
• Optimise SQL, cloud platforms and data warehouse performance.
• Troubleshoot production issues and support critical data services.
• Collaborate with business and technical stakeholders.
• Mentor team members and promote engineering best practices.

Skills

Data engineering

SQL proficiency

Data transformation

Snowflake

Python

Spark

Azure Data Factory

Databricks

Cloud platforms

Data modelling

Data governance

Data quality

Stakeholder engagement

Troubleshooting

Tools

Azure/AWS/GCP environments

Enterprise data platforms

Job description

Whizdom is partnering with a leading consulting organisation to hire an experienced Context Engineer for a major banking program in Australia. This hands-on role focuses on building scalable cloud data solutions, data integration and governance across cloud and on-prem environments.

You will design, develop and optimise batch and near real-time data pipelines using Snowflake, Python, Spark, and Azure Data Factory, collaborating with stakeholders to deliver enterprise-scale data platforms with