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Support Engineer - Data

Primary Function

- Operate, support and maintain cloud-based data solutions, leveraging automation and standardised operational processes.
- Manage cloud environments in accordance with company security guidelines, standards and platform requirements.
- Support, troubleshoot and resolve incidents affecting data applications, pipelines, cloud infrastructure and production services.
- Conduct root cause analysis and problem rectification, implementing corrective and preventative actions to reduce incident recurrence.
- Build, modify and support data pipelines to accommodate operational requirements and changes in data structures.
- Review ETL pipelines, code and deployments from a support and operational perspective to ensure consistency, quality and production readiness.
- Work collaboratively with Engineering, Development and upstream/downstream system teams to resolve production issues and minimise impacts to applications and key SLAs.
- Liaise with business stakeholders, platform teams, cloud vendors and service providers to investigate and resolve application, infrastructure and production issues.
- Maintain and continuously improve support procedures, operational documentation, troubleshooting guides and production best practices.
- Identify gaps in existing support and operational processes and contribute to service, reliability and process improvements.
- Support cloud deployments and production changes, ensuring appropriate operational controls and best practices are followed.




- Provide technical support and guidance to stakeholders on data-platform applications, services and cloud technologies.

Position Description- Data & Cloud Operations Support

- Operate, support and maintain cloud-based data solutions, leveraging automation and standardised operational processes.
- Manage cloud environments in accordance with company security guidelines, standards and platform requirements.
- Support, troubleshoot and resolve incidents affecting data applications, pipelines, cloud infrastructure and production services.
- Conduct root cause analysis and problem rectification, implementing corrective and preventative actions to reduce incident recurrence.
- Build, modify and support data pipelines to accommodate operational requirements and changes in data structures.
- Review ETL pipelines, code and deployments from a support and operational perspective to ensure consistency, quality and production readiness.
- Work collaboratively with Engineering, Development and upstream/downstream system teams to resolve production issues and minimise impacts to applications and key SLAs.
- Liaise with business stakeholders, platform teams, cloud vendors and service providers to investigate and resolve application, infrastructure and production issues.
- Maintain and continuously improve support procedures, operational documentation,



troubleshooting guides and production best practices.
- Identify gaps in existing support and operational processes and contribute to service, reliability and process improvements.
- Support cloud deployments and production changes, ensuring appropriate operational controls and best practices are followed.
- Provide technical support and guidance to stakeholders on data-platform applications, services and cloud technologies.

Work Experience

- Experience working in Cloud Operations, Production Support, Data Operations or a similar technical support environment.
- Demonstrated experience troubleshooting and analysing data pipelines, cloud applications and production workloads.
- Solid understanding of data warehousing concepts, including ETL processes, data reconciliation, error handling and data lifecycle concepts.
- Working knowledge of cloud data platforms and technologies, preferably including Microsoft Azure, Snowflake and Databricks.
- Experience supporting Azure services such as Azure Data Factory, ADLS, Key Vault, Azure Functions and related cloud infrastructure.
- Knowledge of Databricks concepts including clusters, policies, Delta Tables and performance optimisation techniques.
- Strong understanding of Snowflake data warehouse concepts and operational best practices.
- Exposure to workflow orchestration technologies such as Control M and associated operational practices.
- Experience with CI/CD and DevOps processes, including source control and deployment pipelines using technologies such as Git and Azure.
- Working knowledge of programming and query languages such as Python and SQL.
- Experience sup

📌 Data Ops Support Engineer (Melbourne)
🏢 Accenture Australia
📍 Melbourne