Solution Architect, AI and Data, Technology Consulting

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The opportunity   We are seeking a highly skilled Databricks-focused Solution Architect to join our team. In this role, you will work at the forefront of data engineering, analytics and AI, with a specific focus on designing and implementing cloud-based data and AI solutions using the Databricks Data Intelligence Platform and the broader ecosystem of technologies that support modern data and AI architectures.   You will play a key role in defining solution architecture, shaping technical direction and guiding delivery teams to design and build scalable, secure and user-centric data solutions. Your work will span data ingestion and transformation patterns, data modelling, data product design, governance, integration and consumption layers, helping organisations unlock value from their data through analytics, AI and data visualisation capabilities. This position offers the opportunity to lead solution design across complex client environments, provide trusted technical advice to stakeholders, and mentor junior team members while contributing to innovative projects across data, analytics and AI.   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

Lead the design of Databricks solution architectures that support scalable data engineering, analytics, AI and reporting use cases. Define end-to-end data platform and Lakehouse architecture patterns, including ingestion, transformation, modelling, governance, orchestration and consumption layers. Design scalable, secure and robust data ingestion, transformation and analytics solutions using Databricks, Spark, Unity Catalog and related cloud-native services. Translate business, data and analytics requirements into clear solution designs, technical specifications and delivery roadmaps. Provide technical leadership across delivery teams, helping guide design decisions, manage technical trade-offs and ensure solutions align to architecture principles. Support the design of data models, data products and reusable platform patterns that enable reliable analytics and downstream consumption. Integration of the Databricks Data Intelligence Platform with cloud-native and third-party ecosystem toolsets, and enterprise data ecosystems. Collaborate with cross-functional teams to understand data needs and translate them into technical solutions. Stay updated with the latest industry trends and technologies to ensure the team remains at the cutting edge of data engineering, AI and analytics practices.

Skills and attributes for success

Designing and implementing Databricks Lakehouse platforms in complex environments. Data platform solution architecture, including architecture patterns for ingestion, transformation, storage, governance, orchestration and consumption. Data modelling using a range of methodologies to support analytics, reporting and AI use cases. Data engineering and building scalable, robust data pipelines. Writing efficient SQL and Spark-based data processing solutions. Integrating Databricks with cloud-native services, data processing frameworks and enterprise data ecosystems. Engaging with technical and non-technical stakeholders to understand requirements, communicate design decisions and influence solution direction. Providing technical leadership within a delivery environment, including mentoring team members and supporting delivery planning. Writing and reviewing efficient SQL and Spark-based logic, with the ability to guide engineering teams on good development