Senior Data Engineer

• Exposure to complex, mission critical environments
• Hybrid Working Arrangements - 50% WFH
• Contribute to a high-profile government transformation Program

About the Organisation

Our client is a large and complex government organisation undergoing significant digital transformation initiatives to enhance data-driven decision making, operational efficiency, and business intelligence capabilities. The organisation is investing heavily in modern data platforms, data governance, analytics, and cloud technologies to maximise the value of enterprise data assets.

About the Role

We are seeking a highly skilled Senior Data Engineer to join a high-performing Data Engineering team. In this role, you will contribute to the establishment and ongoing support of enterprise-scale data warehouses, cloud-based data lakes, and analytics platforms. You will be responsible for developing and maintaining ETL/ELT pipelines, data integration solutions, automation frameworks, and data engineering capabilities across both on premises and cloud environments. Working closely with Data Governance, Data Science, Business Intelligence, and business stakeholders, you will play a critical role in delivering reliable, scalable, and secure data solutions that support reporting, analytics, operational decision making, and AI/ML initiatives.

Key Accountabilities and Outcomes

• Deliver enterprise-scale data engineering functions and capabilities.
• Establish and maintain data storage platforms for structured and unstructured data.
• Develop and maintain scalable ETL/ELT pipelines within complex operational environments.
• Manage and support on-premises and cloud-based data analytics platforms.
• Design, establish, and maintain enterprise data warehouses and data lakes.
• Source, integrate, and manage data from multiple systems including SQL Server, Oracle, cloud platforms, and APIs.
• Develop and maintain data models to support reporting, analytics, and business intelligence requirements.
• Create and manage SQL and Python-based data workflows.
• Support data integration, orchestration, automation, scheduling, logging, auditing, and version control processes.
• Implement role-based access controls and enterprise data authorisation models.
• Ensure compliance with privacy, confidentiality, security, and data governance requirements.
• Deliver high-quality data solutions for reporting, analytics, data sharing, and business intelligence.
• Support environment management and deployment pipelines across Development, Test, and Production environments.
• Perform platform optimisation and improve data pipeline performance and reliability.
• Undertake testing, validation, and continuous improvement of data pipelines.
• Collaborate with Data Governance, Data Science, and Business Intelligence teams to deliver scalable solutions.
• Maintain comprehensive documentation including business glossaries, semantic layers, data models, data flows, and business rules.
• Apply Git-based version control and CI/CD best practices.
• Work closely with business stakeholders to translate requirements into practical data engineering solutions.
• Mentor junior team members and contribute to capability uplift across the organisation.
• Drive innovation and continuous improvement across data engineering platforms, tools, and practices.

Desired Experience and Capabilities

• Proven experience working as a Senior Data Engineer within large and complex organisations.
• Minimum 5 years' experience developing and maintaining scalable ETL/ELT pipelines.
• Strong experience establishing enterprise data engineering capabilities including data storage, data integration, ETL/ELT, orchestration, automation, logging, auditing, and version control.
• Extensive experience managing structured and unstructured data in enterprise environments.
• Strong expertise in SQL and Python development.
• Proven experience with data warehousing, data lakes, and modern analytics platforms.
• Experience designing and implementing data integration and migration solutions across complex datasets.
• Strong understanding of both on-premises and cloud-based data platforms.
• Experience implementing data governance, security controls, role-based access controls, and data management practices.
• Strong experience applying optimisation techniques to improve platform performance.
• Experience with DevOps, DataOps, CI/CD pipelines, and deployment automation.
• Hands on experience with GitHub, Bitbucket, or similar version control platforms.
• Experience using collaboration and project management tools such as Jira and Confluence.
• Experience supporting data science, machine learning, analytics, and business intelligence workloads.
• Excellent written, verbal, and stakeholder engagement skills.

Preferred Qualifications

• Tertiary qualifications in Information Technology, Computer Science, Data Engineering, Software Engineering, or a related discipline.
• Relevant cloud certifications across Microsoft Azure, AWS, or Google Cloud Platform.
• Experience with modern analytics, machine learning, and AI-enabled data platforms.
• Experience working within highly regulated enterprise or government environments.
• Only Permanent Residents or AU citizens can apply