GCP Data Engineer

Nityo Infotech; Sydney; On-site; AUD 90,000 - 140,000; Full time

Job summary

Nityo Infotech Limited is hiring a Data Engineer in Sydney to design, build, and optimise batch and streaming pipelines using approved frameworks. You will ensure resilience, performance, and cost efficiency, and implement monitoring, alerting, and automated recovery.

You will work with stakeholders to deliver fit-for-purpose data systems, maintain data quality, governance documentation, and CI/CD pipelines for automated testing and deployment. 2-4 years in data engineering preferred.

Qualifications

• Proficient in SQL for data wrangling, transformation, and analysis.
• Experience building ETL/ELT pipelines in cloud or distributed environments.
• Familiarity with cloud platforms and services.
• 2-4 years in a data engineering or closely related role.
• Able to troubleshoot and resolve data pipeline failures or performance issues.
• Communicates clearly and documents work for others to maintain or build upon.

Responsibilities

• Design, build, and optimise batch and streaming data pipelines using approved frameworks and tooling.
• Ensure pipelines are resilient, performant, and cost optimised.
• Implement monitoring, alerting, and automated recovery processes.
• Apply data quality checks and reconciliation processes to ensure accuracy and completeness.
• Maintain metadata, lineage, and documentation to support governance requirements.
• Adhere to role-based access control, data privacy, and security standards.
• Contribute to the development and maintenance of ingestion frameworks, transformation layers, and data models.
• Implement and maintain CI/CD pipelines for automated testing and deployment.
• Optimise data storage and retrieval strategies to meet performance needs.
• Work closely with Technical Leads, Data Architects, Analysts, and business stakeholders to deliver fit-for-purpose solutions.
• Participate in code reviews and knowledge-sharing sessions to improve team capability.
• Explore and adopt new tools, frameworks, and techniques to enhance engineering capability.
• Identify opportunities to automate and streamline workflows.

Skills

SQL

ETL/ELT pipelines

Cloud platforms

Data modeling

Data orchestration

CI/CD

Data quality

Independence

Stakeholder collaboration

Code reviews

Troubleshooting

2-4 years experience

Job description

• Design, build, and optimise batch and streaming data pipelines using approved frameworks and tooling.
• Ensure pipelines are resilient, performant, and cost optimised.
• Implement monitoring, alerting, and automated recovery processes.
• Apply data quality checks and reconciliation processes to ensure accuracy and completeness.
• Maintain metadata, lineage, and documentation to support governance requirements.
• Adhere to role-based access control, data privacy, and security standards.
• Contribute to the development and maintenance of ingestion frameworks, transformation layers, and data models.
• Implement and maintain CI/CD pipelines for automated testing and deployment.
• Optimise data storage and retrieval strategies to meet performance needs.
• Work closely with Technical Leads, Data Architects, Analysts, and business stakeholders to deliver fit-for-purpose solutions.
• Participate in code reviews and knowledge-sharing sessions to improve team capability.
• Explore and adopt new tools, frameworks, and techniques to enhance engineering capability.
• Identify opportunities to automate and streamline workflows.

Key Skills & Experience

• Proficient in SQL for data wrangling, transformation, and analysis
• Experience building ETL/ELT pipelines in cloud or distributed environments
• Familiarity with cloud platforms and services
• Knowledge of data modeling concepts
• Experience with data orchestration tools
• Familiar with version control and CI/CD pipelines
• Understanding of data quality, validation, and observability practices
• Works independently with minimal supervision on well-scoped tasks
• Collaborates effectively with stakeholders
• Communicates clearly and documents work for others to maintain or build upon
• Open to code reviews, feedback, and continuous learning
• Able to troubleshoot and resolve data pipeline failures or performance issues
• 2-4 years in a data engineering or closely related role
• Demonstrated ability to improve code quality, reliability, or performance