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Databricks

Customer Enablement Architect (Capability Engineering & AI Adoption)

Sydney, New South Wales, Australia

Location
Sydney, New South Wales, Australia
Work
Not stated
Employment
Not stated
Level
Lead / staff
Function
Customer success & support
Pay
Not stated
Posted
5 weeks ago

About the role

CSQ427R440

The Databricks Customer Enablement team is on a mission to upskill data and AI professionals in customer organizations so they can use Databricks effectively and accelerate customer success.

As a Customer Enablement Architect, you will design and lead customer enablement and talent-transformation programs across Australia and New Zealand. You will partner with Sales, Field Engineering, Forward Deployed Engineering, Training Delivery, and Operations to understand customer needs, recommend the right learning solutions, and ensure successful execution.

You will balance strategic customer engagement with program and commercial execution across training bookings, revenue, learners, credentials, and adoption. You will bring enough technical depth to understand Databricks curriculum and certifications, make credible recommendations, and engage confidently with technical stakeholders—without being expected to deliver deep hands-on technical training.

The impact you will have

  • Work with regional Go-to-Market teams to create enablement strategies aligned to customer segment, business priorities, technical maturity, and talent-transformation goals.
  • Translate customer outcomes into practical learning plans, capability roadmaps, and recommendations across free and paid training, instructor-led and self-paced learning, credentials, and partner delivery.
  • Partner with global Delivery and Operations teams to coordinate scheduling, communications, program quality, and seamless execution of customer development plans.
  • Manage and report weekly, monthly, and quarterly performance across training bookings, revenue, learners, credentials, and adoption; use insights to guide action from field teams.
  • Serve as the voice of the customer for regional enablement, curriculum, and certification priorities, while engaging senior leaders and executives internally and externally.
  • Identify capability gaps that may affect platform adoption and work with account teams on targeted interventions, including contextual or just-in-time enablement where it improves customer outcomes.

Technical context you will support

You will help customers build capability across areas such as:

  • Lakehouse architecture, data engineering, ETL, data governance, and data quality
  • Databricks training, certifications, and foundational onboarding experiences
  • Generative AI, agentic workflows, Databricks Apps, Genie, and Lakeflow
  • Translating technical adoption needs into accessible enablement and talent-transformation programs

You do not need to be a principal engineer. You should be able to hold a credible technical conversation, understand curriculum and certification requirements, and recommend the right enablement path. Experience creating a prototype, automation, or technical tool is valuable but not required.

What we look for

  • 5+ years of demonstrated experience in Customer Enablement, Talent Transformation, Training, Customer Success, Consulting, or managing a book of business.
  • Hands-on Builder Mindset: A non-negotiable track record of personally designing, building, and deploying working prototypes, automation tools, or technical apps.
  • Experience creating and leading enablement programs in partnership with Sales and technical teams to deliver customer outcomes.
  • Experience in Big Data, AI, Data Science, cloud platforms, or enterprise technology, with the ability to understand technical curricula and certifications.
  • Strong customer and executive engagement skills, including discovery, stakeholder management, presentation, facilitation, and navigating ambiguity.
  • Commercial & Business Insight: Ability to connect technical skill outcomes to core P&L levers, influence renewals/expansions, and collaborate effectively with sales on strategic account planning.
  • Experience operating across ANZ markets, strong operational discipline, and willingness to travel as needed
  • Experience with technical solutioning or building tools is a plus.

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Source

Posted by Databricks on their own hiring page, databricks.com. OptiTalent shows it as published, read 06 Nov 2026 23:57 UTC; the original is the reference.

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