Top Technology Jobs & Startup Jobs in Sydney

Design, develop, and deploy AI, machine learning, and Generative AI solutions for client environments. Build copilots, chatbots, RAG applications, intelligent automation, and AI workflows across enterprise cloud platforms. Collaborate with data engineers, consultants, architects, and stakeholders on solution architecture, technical design, evaluation, governance, and optimization. Translate technical concepts into business outcomes, create reusable accelerators, document solutions, and contribute to consulting engagements.

Designs and maintains scalable data pipelines, ETL/ELT processes, integrations, cloud data platforms, data models, and curated datasets. Implements orchestration, data quality, governance, monitoring, and performance improvements across client engagements. Collaborates with architects, analysts, consultants, and stakeholders to support reporting, business intelligence, AI, and operational outcomes. Contributes to technical discovery, solution design, documentation, reusable frameworks, and consulting delivery standards.

Analyze business and operational data, build Power BI dashboards and reports, validate data quality, support data modeling, and translate findings into actionable business insights. The role involves gathering stakeholder requirements, collaborating with engineers and consultants on analytics projects, preparing documentation, supporting workshops and user acceptance testing, and contributing to improved analytics standards in a consulting environment.

Designs, implements, administers, optimizes, and supports enterprise Microsoft Fabric environments. Responsibilities include data engineering, integration, warehousing, real-time intelligence, Power BI, CI/CD, DevOps, governance, security, monitoring, automation, performance tuning, and cost management. The specialist collaborates with technical teams and clients on architecture, discovery, documentation, and delivery of scalable analytics and AI-ready data platforms.

Designs, architects, configures, secures, optimizes, and supports enterprise Databricks environments. Develops scalable data engineering and analytics solutions, CI/CD pipelines, DevOps automation, governance, monitoring, and cost-management practices. Supports ingestion, transformation, orchestration, streaming, AI, and analytics workloads while collaborating with engineers, architects, consultants, and clients. Participates in technical discovery, stakeholder engagement, documentation, and reusable platform framework development.