Job Description This high profile Government client operates in a highly regulated enterprise environment. They have a contract opportunity available for an experienced Cloud Engineer who has recent hands-on enterprise experience working on large-scale data platforms in Azure. The ideal candidate will be responsible for designing, developing, and deploying scalable, high-performance cloud-based data solutions within complex enterprise environments. This role demands deep expertise in Azure Modern Data Lakes, Data Warehouses, Microsoft Fabric, Synapse Analytics, SQL and PySpark, with strong capabilities in Azure DevOps, CI/CD pipelines, and data warehousing. About the Role Key Responsibilities include: Enterprise-Scale Data Solutions: Design, build, and optimise cloud data solutions using Azure Data Lake, Synapse Analytics, and Microsoft Fabric to support high-volume, batch, and real-time data processing. ETL Pipelines & Data Engineering: Develop and manage enterprise-grade ETL/ELT processes using Azure Data Factory, PySpark, and SQL-based transformation frameworks for seamless data ingestion, transformation, and loading. Data Warehousing & Performance Optimization: develop and maintain robust data warehouse and Lakehouse solutions, ensuring performance, cost-efficiency, and scalability across large datasets. CI/CD & DevOps Integration: Implement and maintain Azure DevOps pipelines to streamline deployment, testing, and integration of data engineering workflows in highly regulated enterprise environments. Collaboration: Work closely with cross-functional teams, including architects, data engineers, analysts, and business stakeholders, to translate business requirements into technical solutions. Security & Governance: Ensure enterprise data security, compliance, and governance using Microsoft Purview or similar, role-based access controls (RBAC) and data lineage tracking. Performance Optimisation: Monitor and optimise data pipelines and storage solutions for performance, reliability, and cost-efficiency. Documentation & Best Practices: Maintain comprehensive documentation for data architectures, pipelines, and workflow processes, adhering to enterprise standards and best practices. The Successful Candidate The ideal candidate will have: Minimum 5 years of hands-on experience in large-scale enterprise data platforms on Azure . Azure Cloud Expertise: Strong proficiency in Azure Data Lake, Synapse Analytics, Microsoft Fabric, and Data Warehousing concepts. ETL & Big Data Processing: Hands-on experience with Azure Data Factory (ADF), PySpark, and high-performance ETL pipelines. DevOps & Automation: Proven expertise in Azure DevOps, CI/CD pipelines, Infrastructure as Code (IaC), and automated deployment strategies. Programming Skills: Proficiency in Python, T-SQL, and/or Scala, with strong data transformation and processing experience. Performance Tuning & Optimization: Ability to troubleshoot and optimise data workflows for scalability, cost efficiency, and high availability. Stakeholder Communication: Strong ability to translate complex technical solutions into business-friendly insights, collaborating effectively with both technical and non-technical stakeholders. What's on Offer Contract term initially until the end of June 2025 Start ASAP Located in St Leonards . This is a fantastic opportunity to work with a well regarded and high profile government agency. The position offers competitive contracting rates. How to Apply Please upload your resume to apply. We will be in touch with further instructions for suitably skilled candidates. Please note that you will be required to complete selection criteria to complete your application for this role. Call Katrina Gabriel or email katrinagwhizdom.com.au for any further information. Candidates will need to be willing to undergo pre-employment screening checks which may include, ID and work rights, security clearance verification and any other client requested checks. Job Description Cloud Engineer EDWARD Contents Job Description – Cloud Engineer 1 Primary purpose of the role 1 Key Responsibilities: 1 Key Accountabilities – Cloud Data Engineer 1 Essential Criteria: 1 Desirable Criteria: 1 Job Description – Cloud Engineer Primary purpose of the role We are seeking an experienced Cloud Engineer with recent hands-on enterprise experience working on large-scale data platforms in Azure . The ideal candidate will be responsible for designing, developing, and deploying scalable, high-performance cloud-based data solutions within complex enterprise environments. This role demands deep expertise in Azure Modern Data Lakes, Data Warehouses , Microsoft Fabric, Synapse Analytics, SQL and PySpark , with strong capabilities in Azure DevOps, CI/CD pipelines, and data warehousing . Key Responsibilities: Enterprise-Scale Data Solutions: Design, build, and optimi s e cloud data solutions using Azure Data Lake, Synapse Analytics, and Microsoft Fabric to support high-volume, batch, and real-time data processing. ETL Pipelines & Data Engineering: Develop and manage enterprise-grade ETL/ELT processes using Azure Data Factory, PySpark , and SQL-based transformation frameworks for seamless data ingestion, transformation, and loading. Data Warehousing & Performance Optimization: develop and maintain robust data warehouse and Lakehouse solutions , ensuring performance, cost-efficiency, and scalability across large datasets . CI/CD & DevOps Integration: Implement and maintain Azure DevOps pipelines to streamline deployment, testing, and integration of data engineering workflows in highly regulated enterprise environments . Collaboration: Work closely with cross-functional teams, including architects, dat a engineers , analysts, and business stakeholders, to translate business requirements into technical solutions. Security & Governance: Ensure enterprise data security, compliance, and governance using Microsoft Purview or similar , role-based access controls (RBAC) and data lineage tracking . Performance Optimisation: Monitor and optimise data pipelines and storage solutions for performance, reliability, and cost-efficiency. Documentation & Best Practices: Maintain comprehensive documentation for data architectures, pipelines, and workflow processes, adhering to enterprise standards and best practices. Key Accountabilities – Cloud Data Engineer Design and Develop Enterprise-Scale Data Pipelines: Design, implement, and optimise ETL/ELT pipelines for Azure-based data platforms, ensuring seamless data ingestion, transformation, and storage for both batch and real-time workloads. Cloud-Native Data Processing & Transformation: Develop and implement high-performance data pipelines using Azure Data Factory (ADF), PySpark , and SQL-based transformation frameworks, adhering to industry best practices. Data Lakehouse & Warehousing Solutions: Work with Azure Data Lake , One Lake , Synapse Analytics, and Microsoft Fabric to design and maintain scalable data warehouses and lake houses . Ensure efficient data storage, retrieval, and management for large datasets. Big Data & Performance Optimization: Analyse , troubleshoot, and optimise data ingestion, storage, and processing pipelines for cost efficiency, high availability, and performance across enterprise-scale workloads. CI/CD & Infrastructure Automation: Develop, test, integrate, and deploy data solutions using Azure DevOps, Git, and Infrastructure as Code ( IaC ), enabling seamless automation and version control. Data Governance & Security: Implement enterprise-grade security policies, access controls (RBAC), and governance frameworks using Microsoft Purview or similar and Azure Security best practices. Ensure compliance with data privacy and regulatory requirements. Collaboration with Cross-Functional Teams: Work closely with data scientists, analysts, engineers, and business stakeholders to translate business requirements into scalable cloud data solutions. Participate in technical discussions and solution design workshops. Enterprise Data Modelling & Architecture: Work with complex data models and integrate structured and unstructured data sources into modern data platforms. Innovation & Continuous Improvement: Stay up to date with emerging cloud technologies and recommend enhancements to improve data engineering workflows, performance, and automation. Documentation & Best Practices: Maintain comprehensive documentation of data architectures, workflows, pipelines, and best practices, ensuring consistency across teams. Essential Criteria: Experience: Minimum 5 years of hands-on experience in large-scale enterprise data platforms on Azure . Azure Cloud Expertise: Strong proficiency in Azure Data Lake, Synapse Analytics, Microsoft Fabric, and Data Warehousing concepts . ETL & Big Data Processing: Hands-on experience with Azure Data Factory (ADF), PySpark , and high-performance ETL pipelines . DevOps & Automation: Proven expertise in Azure DevOps, CI/CD pipelines, Infrastructure as Code ( IaC ), and automated deployment strategies . Programming Skills: Proficiency in Python, T-SQL, and/or Scala , with strong data transformation and processing experience. Performance Tuning & Optimization: Ability to troubleshoot and optimise data workflows for scalability, cost efficiency, and high availability . Stakeholder Communication: Strong ability to translate complex technical solutions into business-friendly insights, collaborating effectively with both technical and non-technical stakeholders . Desirable Criteria: Certifications: Microsoft Certified: Azure Data Engineer Associate , Microsoft Certified: Fabric Data Engineer Associate or equivalent certifications. Agile Methodologies: Experience working in Agile delivery environments. Data Modelling & Governance: Familiarity with data modelling techniques, data governance, and security best practices . Big Data Ecosystem: Exposure to Delta Lake, Databricks, and other big data technologies within the Azure ecosystem . Job Description - Cloud Engineer Page 1 of 1