Recruiting the Modern Data Stack.

We are looking for an experienced Databricks Data Architect to join a major data platform initiative in Canberra. This is a senior architecture role focused on the design and evolution of a modern Databricks-based data platform, working across data architecture, engineering, integration, governance and security. Key Responsibilities Design and evolve enterprise data architecture using Databricks. Define scalable data platform patterns, standards and frameworks. Design data structures, models and integration patterns across complex source systems. Provide architectural guidance to Data Engineering teams. Establish best practices across ingestion, transformation, storage and consumption. Design appropriate data governance, lineage, security and access controls. Work closely with engineering, infrastructure and business stakeholders. Ensure the platform is scalable, secure and maintainable. Key Skills Strong Databricks architecture experience. Experience designing enterprise-scale cloud data platforms. Strong understanding of Lakehouse / Medallion architecture. Unity Catalog and data governance experience. Strong Spark / PySpark and SQL knowledge. Data modelling and enterprise data architecture. Cloud data engineering and integration patterns. Experience designing secure and governed data environments. Strong stakeholder engagement and technical leadership. An active NV1 security clearance is required for this opportunity.

Working with a large enterprise organisation to build an AI-enabled supply chain monitoring capability, connecting data across the organisation to provide better visibility, insight and early identification of issues. Core focus: Building the data and AI foundations for enterprise supply chain monitoring Connecting fragmented data sources into a governed, scalable cloud data platform Using Snowflake, dbt and Power BI to create trusted, accessible enterprise data Deploying Snowflake Cortex and Cortex Analyst to enable natural language interrogation of operational and supply chain data Using AI to monitor supply chain activity, identify risks, surface anomalies and provide actionable insights Delivering self-service analytics through AWS QuickSight Integrating enterprise GenAI tools including Claude and Snowflake Cortex Establishing AI governance, security and risk controls to support responsible adoption at scale Tech: Snowflake, Snowflake Cortex, Cortex Analyst, dbt, Power BI, AWS QuickSight, Claude, AWS, GenAI.

We are looking for an experienced Data Engineer to join the second phase of a major enterprise AWS data platform project. This is a hands-on engineering role for someone who enjoys writing code, building production data pipelines and developing scalable data engineering frameworks. Key Responsibilities Design and build production-grade data pipelines on AWS. Develop and maintain workflows using Apache Airflow / MWAA. Build data processing solutions using Python and PySpark. Develop ELT transformations using dbt and SQL. Work across AWS Glue, S3, Redshift and related AWS services. Build reusable engineering components and frameworks. Troubleshoot, optimise and support production pipelines. Key Skills Strong AWS Data Engineering experience. Hands-on Apache Airflow / MWAA. Strong Python / PySpark. Excellent SQL. AWS Glue and/or EMR. dbt experience. Amazon Redshift experience highly regarded. Experience building and supporting production data platforms. Initial six-month contract with potential to extend.

Lead the architecture of a modern Snowflake platform supporting a major on-premise-to-cloud data migration.

Senior consulting role leading Databricks architecture, solution design and client advisory across modern data platform programs (No sales )

Lead a small delivery squad modernising data pipelines and platform engineering practices for a national organisation.