Join Accenture’s Data & AI practice and help build the next generation of AI‑ready data platforms on Databricks. We’re investing heavily to lead in GenAI, Data & AI, and we bring that momentum to real client outcomes across ANZ. As Accenture, we are Databricks’ largest partner and have earned Global GSI Partner of the Year recognition 7 years in a row (2019–2025) and APJ Industry Leader Partner of the Year 2025 You’ll work alongside one of the largest certified Databricks teams in ANZ, supported by a strong local bench and global delivery scale -designing, modernizing, and accelerating data journeys with proven assets and accelerators that move clients faster from strategy to implementation.

Key Skills Databricks & Lakehouse Expertise - Solid hands-on experience with the Databricks Lakehouse Platform, including:

- Delta Lake and practical use of Delta Live Tables (DLT) for pipeline development - Unity Catalog for data governance, access control, and data organization - Workflows and job orchestration for production-grade pipelines - SQL Warehouses for analytics and performance-optimized querying - Working exposure to advanced capabilities such as AI/BI features and agent-based workflows, with ability to apply them in client scenarios Data Engineering - Proven experience designing and implementing ETL/ELT pipelines across batch and streaming workloads - Robust understanding of data modelling techniques, data quality frameworks, and end-to-end pipeline lifecycle management - Ability to apply modern data architecture patterns,



including data products and domain-oriented data design Programming & Distributed Processing - Strong proficiency in Python and SQL for building scalable data pipelines - Hands-on experience with PySpark (or equivalent) for distributed data processing - Experience working with both batch and streaming pipelines, including performance optimization - Applies coding best practices, testing, debugging, and code modularity in production environments Cloud & Ecosystem - Practical experience working with at least one cloud platform (Azure, AWS, or GCP) - Hands-on exposure to cloud-native data services (e.g. storage layers, orchestration tools, ingestion services) - Familiarity with APIs and integration patterns for connecting enterprise data systems Development Practices & Tooling - Working experience with version control (Git) and CI/CD pipelines in data engineering contexts - Applied understanding of DataOps and DevOps practices for reliable and repeatable deployments - Experience contributing to deployment automation and release management in Lakehouse environments Collaboration & Professional Growth - Ability to work independently on defined tasks while collaborating effectively with architects and senior engineers - Strong communication skills with experience engaging both technical and business stakeholders - Demonstrates ownership of deliverables and contributes to problem-solving in client engagements - Proactive in continuous learning, certifications, and staying current with Databricks and cloud ecosystem advancements.

📌 Databricks Engineer (Brisbane)
🏢 Accenture
📍 Brisbane