Role & responsibilities :

- Use AI tools such as Databricks Genie and Cursor as core, everyday parts of your engineering workflow, not as occasional add-ons.

- Act as an out-of-the-box thinker, proactively identifying new, AI-driven ways of working that differ from the team's current, more conventional methods.

- Apply AI to find, analyze, and triage issues and problems across Databricks pipelines, jobs, and platform components faster than traditional manual methods.

- Design and implement efficient, AI-assisted approaches to resolve issues, optimize workflows, and reduce time-to-resolution.

- Lead the architecture, design, and hands-on build of Databricks-based data and AI solutions.

- Bring in and champion modern engineering practices that combine deep Databricks expertise with AI-assisted development and analysis.

- Collaborate closely with engineering teams to demonstrate, document, and scale the AI-driven ways of working you introduce.

- Provide technical leadership, mentoring, and direction to other engineers on both Databricks best practices and AI-assisted engineering techniques.

Preferred candidate profile :

- 10+ years of overall technology experience, with substantial hands-on experience on the Databricks platform (architecture, development, and/or technical leadership).

- Demonstrated hands-on use of AI tools in real engineering work, ideally including Databricks Genie and/or Cursor (or directly comparable AI coding/analysis assistants).

- Proven ability to design, build, and troubleshoot Databricks pipelines, jobs, clusters, and related data engineering or data platform components.

- A track record of challenging or improving existing engineering processes rather than simply following established playbooks.

- Strong problem-solving skills, with the ability to use AI tools to accelerate root-cause analysis and issue resolution.