Databricks Solution Architect

luvo Talent; Sydney; Hybrid; AUD 240,000 - 320,000; Full time

Benefits offered by this job

Competitive salary

Hybrid work model

Job summary

luvo Talent is seeking a senior Databricks Solution Architect to join its enterprise Data & AI practice in Sydney on a permanent hybrid arrangement. You will design, lead and deliver Databricks Lakehouse solutions across AWS, Azure and GCP, working with business and technology stakeholders to drive large-scale cloud analytics transformations.

The role focuses on architecting end-to-end platforms, mentoring engineering teams, and guiding production deployments while optimizing performance and

Qualifications

• 10+ years in technology consulting, data engineering or analytics.
• 7+ years delivering enterprise data platforms and solutions.
• Proven delivery of 6-8 enterprise Databricks implementations.
• Strong architecture across AWS, Azure or GCP.
• Stakeholder engagement and customer-facing consulting skills.

Responsibilities

• Design enterprise-scale Data & AI solutions on the Databricks Lakehouse Platform.
• Define end-to-end architecture across cloud-native environments.
• Lead Databricks implementations from discovery through to production deployment.
• Build scalable ETL/ELT with Apache Spark and Delta Lake.
• Collaborate on CI/CD pipelines, Infrastructure as Code and deployment automation.
• Mentor engineering teams and establish governance best practices.

Skills

Databricks Lakehouse

Apache Spark

Cloud architecture

Stakeholder engagement

Mentoring teams

Tools

Terraform

CI/CD pipelines

Infrastructure as Code

Job description

Position

We're looking for a Databricks Solution Architect to join a growing enterprise Data & AI consulting practice delivering large-scale cloud and analytics transformation programs.

Job Details

• Permanent role
• Sydney Hybrid arrangment
• Competitive salary

This is a senior, hands-on architecture role where you'll design, lead and deliver enterprise Databricks Lakehouse solutions across AWS, Azure and GCP. You'll work directly with business and technology stakeholders, lead architecture workshops and guide engineering teams through successful production delivery.

You'll play a key role across solution design, customer engagement and enterprise delivery, including:

• Designing enterprise-scale Data & AI solutions on the Databricks Lakehouse Platform.
• Defining end-to-end solution architecture across cloud-native environments.
• Leading Databricks implementations from discovery through to production deployment.
• Building scalable ETL/ELT frameworks using Apache Spark and Delta Lake.
• Optimising platform performance, scalability and cost.
• Designing secure data platforms with strong governance and security controls.
• Collaborating with engineering teams on CI/CD pipelines, Infrastructure as Code and deployment automation.
• Supporting enterprise MLOps and modern AI workloads.
• Leading technical workshops and architecture sessions with customers and executive stakeholders.
• Mentoring engineering teams and establishing architecture and governance best practices.

Essential Experience

• 10+ years in technology consulting, data engineering or analytics.
• 7+ years delivering enterprise data engineering or data platform solutions.
• Proven delivery of 6-8 enterprise Databricks implementations in production environments.
• Strong architecture experience across AWS, Azure or GCP.
• Deep understanding of Apache Spark, Delta Lake and distributed data processing.
• Experience designing modern enterprise data platforms and cloud-native architectures.
• Strong stakeholder engagement and customer-facing consulting skills.

Highly Regarded

• Azure, AWS or GCP certifications.
• Experience with Infrastructure as Code and DevOps.
• MLOps and AI platform integration experience.

Mandatory Certifications

• Databricks Data Engineer Professional
• Databricks Solution Architect Champion (Databricks recognised)

Why This Role?

• Architect modern Databricks Lakehouse platforms.
• Influence technical direction with senior stakeholders.
• Lead large-scale production implementations.
• Work across cloud-native data engineering, AI and platform modernisation initiatives.
• Mentor engineering teams and help shape enterprise architecture standards.