Melbourne Position Purpose The Cloud Data Operations Engineer is a hands-on technical role focused on building and enhancing cloud-native data quality, profiling, and observability frameworks. Working within a small, collaborative team, this role supports the delivery of trusted, secure, and well-governed data assets across the enterprise. The successful candidate will bring a strong engineering mindset, a passion for data quality, and the ability to design scalable solutions that support both technical and business stakeholders. This is a greenfield opportunity to shape foundational data capabilities, with significant scope for strategic thinking, creativity, and innovation. Key Responsibilities Design, build, and enhance serverless and container-based data quality and profiling frameworks on AWS. Develop automated pipelines for data validation, classification, and observability across Redshift, Databricks, and other platforms. Integrate data quality outputs into reporting and cataloging tools such as Power BI and Alation. Implement and support third-party SaaS data quality agents within cloud infrastructure and CI/CD pipelines. Ensure secure handling of sensitive and classified data, including access control auditing and compliance with data governance policies. Build and maintain robust CI/CD pipelines with integrated testing for infrastructure and application code using Azure DevOps and Terraform. Develop and deploy containerized applications using AWS EKS and ECS. Collaborate closely with team members and stakeholders to align solutions with business needs and technical standards. Produce clear, user-friendly documentation including requirements, designs, and support materials. Contribute to a culture of continuous improvement, knowledge sharing, and operational excellence. Key Skills and Experience Proficiency in Python and YAML for data engineering and configuration-driven development. Strong experience with AWS services, particularly EKS, ECS, Lambda, S3, and Glue. Experience with container development and orchestration using Docker and Kubernetes. Familiarity with data quality tools such as Soda Core or similar. Experience with CI/CD pipelines and infrastructure-as-code using Azure DevOps and Terraform, including automated testing practices. Solid understanding of data engineering pipelines and data warehouse architectures. Experience with RBAC and access control auditing in cloud data environments. Exposure to advanced pattern recognition techniques (e.g., ML, fuzzy logic, Gen AI) is highly desirable. Strong documentation and communication skills, with the ability to work effectively in a collaborative, fast-paced environment. Desirable Attributes Experience working with sensitive or regulated data, including privacy and compliance considerations. Familiarity with data cataloging platforms (e.g., Alation) and business-friendly configuration tools. Ability to work independently while contributing to a highly collaborative team culture. A proactive mindset with a passion for automation, data quality, and scalable design. If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now. If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion on your career. 2994555
