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Tier-1 brand and remote posting increase applicants, but extreme seniority and niche Databricks expertise reduce competition.
Heavily specialized big data and Databricks expertise makes cross-industry transferability low.
Explicit 15+ years and mandatory Databricks, cloud, and Python/Scala experience make filters highly stringent.
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Lead design, build, and deployment of scalable big data and AI applications for strategic customers using the Databricks platform.
Create reference architectures, how-to guides, production-ready tools, and automation utilities for multiple customers across cloud environments.
Manage multiple customer projects concurrently ensuring well-architected principles, risk mitigation, and successful adoption of Databricks solutions.
15+ years experience with Big Data Technologies including Apache Spark, Kafka, Cloud Native, and Data Lakes in customer-facing post-sales, technical architecture, or consulting roles.
6+ years of independent experience working on Big Data Architectures.
2+ years of experience with AI implementations such as RAG, MCP, and Context Engineering.
Proficiency in Python or Scala and experience across cloud platforms (GCP/AWS/Azure).
Strong product development mindset with proven ability to deliver robust, scalable automation utilities and solutions usable across multiple customers.
Experienced in technical architecture and consulting roles with excellent stakeholder management skills in complex, multi-cloud big data environments.
Skilled in problem-solving and translating business problems into reliable technical products specifically within AI and big data domains.