Job Description & Details
This is a high-impact leadership role sitting at the intersection of enterprise architecture, client advisory, and executive business growth in the Bay Area. If you enjoy talking system design with CXOs one minute and rolling up your sleeves to troubleshoot a Databricks or Snowflake pipeline the next, this gig gives you the autonomy to actually drive modernization rather than just talk about it.
What You'll Actually Be Doing
You will act as the principal bridge between enterprise clients, sales teams, and technical delivery squads. Your day-to-day involves designing end-to-end data and AI roadmaps, unblocking tricky cloud-native architectures, and helping scale modern AI and Agentic AI solutions. Expect to spend a lot of time defining strategy for large accounts, building reusable accelerators, and ensuring that what gets sold during pre-sales actually gets built successfully in production.
The Core Tech Stack
You need deep fluency in modern cloud data platforms like Azure, Databricks, Snowflake, and Microsoft Fabric, alongside a solid grasp of modern AI/ML frameworks. The company relies on these technologies to build scalable transformation pipelines and next-gen AI solutions, so you'll need to speak this stack fluently to gain the instant credibility required with both internal engineering squads and enterprise-level stakeholders.
Interview Expectations
Expect the hiring team to test both your high-level strategy and your technical depth. They will likely ask you to walk through how you would architect a real-time data and AI platform for an enterprise client transitioning from legacy on-prem systems, looking closely at how you handle data governance, scale, and cost optimization. They are secretly trying to figure out if you can translate complex technical realities into business value that a skeptical CFO or CIO will actually buy into.
Application Advice
To get past the ATS and grab the recruiter's attention, make sure your resume heavily emphasizes your enterprise consulting background, CXO-level stakeholder management, and hands-on architecture experience with platforms like Databricks, Snowflake, or Azure. Weave in metrics related to large-scale data transformations, pre-sales wins, and AI solution adoption so they immediately see you as a revenue-driving technical leader.