Databricks Engineer
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
Strong 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.
Benefits of working at Accenture:
· 18 weeks paid parental leave
· Long & short-term career break opportunities
· Structured career development program
· Local and international career opportunities.
· Certified as a Family Inclusive Workplace™
· Flexible Work Arrangements - centered around Accenture’s Truly Human ethos and our commitment to supporting the health and wellbeing of our people.
· We are proud to be in the top 3 of last year’s Diversity & Inclusion Index!
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