Data Engineer
Vor 7 Tagen
Get AI-powered advice on this job and more exclusive features. Halo Labs is a future focused, end-to-end data solutions firm - transforming tomorrow, today. Our intelligent and secure technology systems and data driven solutions drive meaningful outcomes and unlock lasting value. Why work at Halo Labs? Leading Innovation: We don't just solve problems; we illuminate a never-ending stream of innovation. Exceptional Perks: Enjoy outstanding perks like a dedicated learning budget, performance bonuses, and comprehensive wellbeing support. Remote-First Organisation: Experience the perks of remote work while having the flexibility to travel to client locations throughout Australia. Inclusive and Engaging: Celebrate diversity in a welcoming space that thrives on new ideas and open conversations, all in a respectful environment. Inspiring Origins: With a compelling founder story, we are a customer-focused, culture-first organisation. About the Role Framework Development: Design, develop, and enhance in-house PySpark frameworks to ensure standardised implementations and promote reusability across projects. Mentorship: Provide technical guidance and mentorship to junior team members, fostering skill development within the analytics community. Stakeholder Collaboration: Collaborate with internal and external stakeholders to deliver high-quality, data-driven solutions that meet business needs. Data Analysis & Engineering: Conduct exploratory data analysis and design end-to-end data engineering solutions, including ETL / ELT pipelines using Azure Data Framework, Databricks, and other Azure services. Pipeline Implementation: Build, test, and deploy scalable data pipelines using Python, PySpark, and Azure services, ensuring adherence to best practices for automated testing, documentation, and CI / CD via Azure DevOps (Git, Azure Pipelines). Platform Monitoring: Monitor and support batch operations for the Data and Insights Platform, ensuring reliability and performance. About You Cloud Expertise: Hands‑on experience with Azure Cloud Services, including Databricks, Azure Data Factory, Azure SQL Server, and Azure Storage. Databricks Proficiency: Strong experience with Databricks for big data processing; leveraging Databricks notebooks for collaborative data engineering and analytics; utilising Databricks clusters for scalable and efficient data processing. Data Engineering Tools: Proficiency in SQL, Python, and PySpark for data processing and pipeline development. Data & Analytics Concepts: Strong understanding of data warehousing, data lakes, ETL / ELT processes, and visualisation / reporting tools (Power BI, Tableau) to drive business value. Data Architecture: Deep knowledge of data architecture, data modelling, data marts, and metadata management best practices. Modern Data Platforms: Minimum 3 years of experience working with modern data platforms (AWS, Azure) and data engineering, with a focus on Agile delivery methodologies. DevOps Practices: Expertise in Azure DevOps, including Git for version control and Azure Pipelines for CI / CD. Education: Degree in Computer Science, Data Science, IT, or a related field. Location: Queensland-based candidates are preferred; outstanding applicants from other locations will also be considered. Job Details Seniority level: Mid‑Senior level Employment type: Full‑time Job function: Information Technology Industries: Business Consulting and Services #J-18808-Ljbffr
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Data Engineer
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vor 13 Stunden
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Senior Data Engineer
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Senior Data Engineer
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