Responsible to find solutions to customers' biggest challenge in big data, analytics, data engineering and data science problems and guide the technical evaluation phase in a hands-on environment throughout the sales process; Serve as a technical advisor internally to the sales team and work with the product team as an advocate for customers in the field; help customers to achieve tangible data-driven outcomes through the use of Databricks Lakehouse Platform. Detailed job duties include: Work with the customers to understand the business and technical requirements; Develop success criteria to evaluate Databricks; Develop a project plan to execute the evaluation; Continue to advise and manage the Databricks implementation; Consult on Big Data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects; Build references architectures, how-tos, and demo applications for customers; Create demonstrations as small prototype applications in Databricks to provide examples for customers; Provide escalated level of support for critical customer operational issues, including diagnosis open customer issues, document and manage risks during the engagement, escalate issues to the engineering team as needed and triage and prioritize feature requests; architect, implement, and/or validate integrations with cloud services or 3rd party applications; Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars. $121,597 - $150,000 per year. Minimum job requirements: Master’s degree in Computer Science, Data Science, Mathematics, Information Technology, Information Science or a related field and at least two years of experience. Must have experience in the following areas: programing experience using at least one of the following languages: Python, Scala, Java, SQL or R; experience building solutions with at least one of the following public cloud providers: AWS, Azure or GCP; Experience with Big Data technologies, including at least one of the following: Spark, Hadoop, Kafka, OLTP, OLAP, DSS, Pandas, Scikit-learn or HPO. May telecommute from any US location.