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Tier-1 brand and metro locations increase applicant density, though role is senior and specialized.
Deep data/AI and cloud architecture requirements make cross-industry transferability low.
Explicit 12+ years and mandatory big-data, cloud, and enterprise customer-facing experience.
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Serve as a trusted technical advisor for named strategic enterprise accounts, managing architecture decisions in data, AI/ML, and platform engineering.
Design and implement AI, GenAI, ML, and modern Lakehouse architectures using Databricks Data Intelligence Platform, including proofs of concept and integration with cloud and third-party tools.
Collaborate with sales to develop and execute account strategies, drive Databricks adoption, influence product roadmap, and contribute to open-source communities relevant to the platform.
12+ years in data engineering, data science, technical architecture, or similar pre-sales/consulting role.
8+ years hands-on experience with Big Data and AI technologies including Apache Spark, data engineering, data science, and AI/ML workloads.
Experience with large enterprise or Fortune 500 customers; multi-geography account support preferred.
Proficient coding experience in Python, SQL, Scala, Java, or R and hands-on with at least one public cloud platform (AWS, Azure, or GCP). Travel availability for regional and occasional international visits.
Experienced in architecting and building end-to-end distributed data and AI solutions with direct implementation involvement, not just advisory roles.
Proven success working with large global accounts, particularly in data-intensive or digital-native/SaaS enterprises with mature AI practices.
Comfortable collaborating cross-regionally and influencing product direction while participating in open-source projects linked to the Databricks ecosystem.