About this role
Technical leaders coordinate multi-workload platforms, enterprise-wide migrations, real-time systems, and AI and machine learning initiatives at scale while acting as the definitive authority for major accounts. Professionals in this group shape consumption strategy, lead competitive positioning against rival platforms, and build senior-level relationships to guide enterprise data and artificial intelligence planning. Mentoring junior staff and contributing to field engineering thought leadership are regular components of the position.
Databricks maintains this opening in Sydney to support the organization's most intricate customer engagements on the Data and AI Platform. Candidates who combine strong engineering capabilities with executive presence and a recognized technical specialization tend to succeed in driving platform adoption and revenue growth.
What you will do
- Manage technical and consumption strategies for the most complex customer accounts to influence platform adoption and revenue growth.
- Act as a trusted advisor on enterprise data and AI strategy by owning senior-level technical relationships.
- Design and execute architecture engagements covering multi-workload platforms, enterprise migrations, real-time systems, and large-scale AI and machine learning.
- Function as a platform expert with a declared archetype to mentor colleagues and drive horizontal impact across the regional team.
- Formulate competitive strategies that position the platform against incumbent and emerging market alternatives.
- Coordinate cross-functional groups including data science specialists, solution architects, partners, and product teams to deliver enterprise-grade solutions.
- Coach junior team members on technical depth, customer engagement methods, and use case prioritization.
What you need
- Bring at least eight years of professional background in solutions architecture, principal engineering, technical pre-sales leadership, or senior customer-facing technical roles.
- Demonstrate expert-level coding proficiency in Python and SQL alongside Spark or PySpark, supported by a live coding assessment and platform build during evaluation.
- Possess deep expertise in enterprise data architecture, distributed systems at scale, streaming and real-time processing, lakehouse design patterns, data governance frameworks, and cloud-native platforms.
- Show expert-level knowledge of the Databricks Platform or equivalent depth in competing technologies with demonstrated rapid learning capability.
- Maintain a declared technical specialization with recognized depth in areas such as real-time architectures, ML and AI platforms, data governance, or large-scale migrations.
- Display a proven track record of driving consumption growth and platform adoption within large accounts.
- Exhibit executive presence with the ability to influence directors, vice presidents, and C-level stakeholders on long-term data and AI strategy.
- Hold a bachelor's or master's degree in computer science, engineering, or a quantitative discipline, or possess equivalent practical experience.
Nice to have
- Databricks certifications
- Prior experience at Databricks, Snowflake, AWS, Google, Microsoft, or a top-tier data and AI company
- Published thought leadership through blogs, conference talks, or open source contributions
- Industry vertical expertise with executive-level domain credibility
Skills and tech stack
Questions candidates ask
What level of experience is required for this role?
Candidates must have eight or more years of experience in solutions architecture, principal engineering, technical pre-sales leadership, or a senior customer-facing technical role. A bachelor's or master's degree in computer science, engineering, or a quantitative discipline is also expected, though equivalent experience is accepted.
What does the interview process involve?
The evaluation process includes a live coding assessment and a platform build. Candidates are tested on expert-level coding proficiency and platform familiarity.
Where is the position located?
This full-time job is based in Sydney, Australia. Databricks is headquartered in San Francisco with over thirty offices around the globe.