Data Engineer

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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, includingDatabricks, Azure Data Factory, Azure SQL Server, and Azure Storage.
• Databricks Proficiency: Strong experience withDatabricksfor 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

While Queensland-based candidates are preferred, outstanding applicants from other locations will also be considered.

You're interested in this exciting opportunity and feel you're the right fit please click "apply"

Seniority level

• Seniority levelMid-Senior level

Employment type

• Employment typeFull-time

Job function

• Job functionInformation Technology
• IndustriesBusiness Consulting and Services

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