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Databricks Engineer

Accenture -
Melbourne VIC

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Job Details

Full-time

Benefits

On-the-job training
Parental leave

Qualifications

CI/CD
Data modelling
Azure
Management
Deployment
DevOps
Git
Google Cloud Platform
SQL
AWS
Release management
Data pipeline
Unity
APIs
Scalability
AI
Communication skills

Full Job Description

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!

We are a WORK180 Endorsed Employer, to see our benefits and policies click here

All our consulting professionals receive comprehensive training covering business acumen, technical and professional skills development. You’ll also have opportunities to hone your functional skills and expertise in an area of specialization. We offer a variety of formal and informal training programs at every level to help you acquire and build specialized skills faster. Learning takes place both on the job and through formal training conducted online, in the classroom, or in collaboration with teammates. The sheer variety of work we do, and the experience it offers, provide an unbeatable platform from which to build a career.

Accenture is a an EEO and Affirmative Action Employee of Females/Minorities/Veterans/Individuals with Disabilities.

Equal Employment Opportunity Statement for Australia:

At Accenture, we recognise that our people are multi-dimensional, and we create a work environment where all people feel like they can bring their authentic selves to work, every day.

Our unwavering commitment to inclusion and diversity unleashes innovation and creates a culture where everyone feels they have equal opportunity. Our range of progressive policies support flexibility in ‘where’, ‘when’ and ‘how’ our people work to ensure that Accenture is an organisation where you can strive for more, achieve great things and maintain the balance and wellbeing you need.

We encourage applications from all people, and we are committed to removing barriers to the recruitment process and employee lifecycle. All employment decisions shall be made without regard to age, disability status, ethnicity, gender, gender identity or expression, religion or sexual orientation and we do not tolerate discrimination. If you require adjustments to the recruitment process or have a preferred communication method, please email [email protected] and cite the relevant Job Number, or contact us on +61 2 9005 5000.

To ensure our workplace is inclusive and diverse we are setting bold goals and taking comprehensive action. To achieve these goals, we collect information that allows us to track the effectiveness of our Inclusion and Diversity programs. Learn how Accenture protects your personal data and know your rights in relation to your personal data. Read more about our Privacy Statement.

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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.