Okay, I've searched for Delivery Solutions Architect roles in Pittsburgh that emphasize customer success, require over 5 years of experience in Data and AI, offer hybrid work modes, and require strong skills in Python. I've found 27 positions that match your criteria.

Sure. Here's the analysis:

Job Analysis:

The Delivery Solutions Architect (DSA) role at Databricks is fundamentally designed to bridge the gap between the technical and commercial aspects of the business, specifically targeting Digital Native customers. The core responsibility of this position is to drive growth and ensure customer success by managing complex customer engagements and providing technical guidance throughout the customer lifecycle. This includes post-sale technical leadership, orchestrating multiple internal teams to create tailored strategies for onboarding and increasing product adoption, and being the go-to resource for technical issues related to Databricks platforms. Candidates will face challenges such as navigating customer expectations, addressing technical complexities, and ensuring that the customers derive optimal value from their investments in Databricks solutions. Success in this role would be characterized by effective stakeholder management, smooth transition of projects from the sales phase to operational success, and measurable growth in both customer satisfaction and product usage. Ultimately, a candidate who can leverage both their technical expertise and interpersonal skills will thrive in this position, driving substantial impact within the organization and its customers.

Company Analysis:

Databricks operates within the competitive landscape of data and AI solutions, positioning itself as a leader that provides a comprehensive data intelligence platform. This unique positioning not only requires a powerful technical foundation, represented by the innovative technology originated from Apache Spark, Lakehouse, and Delta Lake, but also an adaptive approach towards servicing over 10,000 organizations globally. In terms of culture, Databricks appears to value a dynamic, innovative environment where collaboration and inclusivity are prioritized. Such a culture can have profound implications for a role like DSA, where success hinges on building relationships across departments and with customer stakeholders. Given that the DSA is situated within the Field Engineering organization, they are likely to have significant visibility with leadership while also operating at a cross-functional level. Strategically, this role is positioned as a crucial enabler of growth, expected to not only facilitate the initial adoption of the platform but also to identify and execute on opportunities for expanded usage, ultimately aligning with Databricks' long-term vision of unifying and democratizing data analytics and AI on a global scale.

Absolutely. Here are some mock interview questions that could come up:

• Tell me about a time when you successfully led a technical project from inception to completion. What challenges did you face and how did you overcome them?
• Describe a situation where you had to manage a complex customer issue. How did you navigate the situation and what was the outcome?
• Can you provide an example of how you have contributed to a successful pre-sales process in a technical capacity?
• Discuss a time when you had to balance multiple stakeholders’ interests in a project. How did you ensure all parties were satisfied while achieving project goals?
• How would you approach a new customer who is hesitant to maximize their use of the Databricks platform?
• What strategies would you implement to increase adoption of Databricks’ Lakehouse vision among clients?
• Could you explain how you would conduct a discovery workshop with a potential client to identify their data needs?
• Imagine you are tasked with onboarding a large client with multiple use cases. What steps would you take to ensure a smooth transition to using Databricks?
• How do you prioritize tasks when managing multiple accounts with varying complexities?
• What do you find most compelling about Databricks’ mission and values, and how do they resonate with your personal career goals?
• Why do you believe the role of Delivery Solutions Architect is critical in the data AI landscape, particularly for digital-native businesses?
• What metrics or KPIs do you believe are essential for keeping track of a client's success with Databricks, and why?
• How do you see the future of data intelligence evolving, and what role do you think Databricks will play in that future?
• What questions do you have about the collaboration between the Field Engineering team and other departments at Databricks?
• Can you share your thoughts on how to foster diversity and inclusion within technical teams in high-growth environments?