Databricks Platform Engineer, AI and Data, Technology Consulting

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The opportunity   As a Databricks Platform Engineer, you will design, build and optimise scalable cloud-based data platforms that support advanced analytics, AI and data engineering workloads. Working closely with data engineers, architects, and business stakeholders, you will play a key role in enabling secure, high-performing and reliable Databricks environments that drive business outcomes. You will bring experience across modern cloud ecosystems and the Databricks Data Intelligence Platform, contributing to the design, implementation and operation of enterprise data and AI platforms. Your work will include platform configuration, automation, security, governance, monitoring and performance optimisation, helping teams build and run data workloads with confidence. You will also support team delivery, providing technical leadership and guidance where required.   This is a hybrid position that can be based in Naarm – Melbourne, Meanjin – Brisbane or Warrang – Sydney . Our roles can potentially be adjusted to work flexibly with reduced hours. Please speak with us about potential options.   Your key responsibilities

Design, build and maintain scalable Databricks-based data platforms across Azure or AWS. Configure and manage Databricks workspaces, clusters, jobs, workflows, permissions and platform services to support data engineering, analytics and AI use cases. Support the implementation of Lakehouse architectures using Databricks, Apache Spark, Delta Lake, Unity Catalog and related cloud-native services.Develop and maintain infrastructure-as-code, CI/CD pipelines and automation to support repeatable, reliable platform delivery. Implement platform security, access controls, governance, monitoring and operational standards across cloud and Databricks environments. Work with data engineers, AI engineers, and architects to design and implement platform patterns which support ingestion, transformation, orchestration, storage and consumption requirements. Troubleshoot platform issues across Databricks, Spark and cloud services, working with technical teams to resolve incidents and improve stability. Document platform designs, configuration patterns, operational processes and technical standards. Support and guide team members, contributing to delivery planning and technical direction.

Skills and attributes for success

Strong experience designing and implementing cloud-based data platforms (Azure and/or AWS) Hands-on experience working with the Databricks Data Intelligence Platform, including workspace configuration, compute management, jobs, workflows and platform administration activities. Proficiency in Databricks, Apache Spark, Delta Lake, Unity Catalog and related data engineering technologies Experience supporting secure and governed data platform environments, including identity, access management, permissions, secrets, networking and data governance controls.Knowledge of infrastructure-as-code and DevOps practices (e.g. Terraform, CI/CD pipelines, Git-based workflows and automated deployment processes). Experience implementing platform security, governance and monitoring frameworks. Strong problem-solving and analytical capability, with a practical approach to working through technical issues. Excellent communication skills with the ability to engage technical and non-technical stakeholders. Experience contributing to or leading delivery within a team environment, including working with engineers, architects and stakeholders to achieve shared outcomes.

Ideally, you’ll have the skills and attributes below, but don’t worry if you don’t tick all the boxes. We’re interested in your aptitude, attitude and willingness