Senior Solutions Engineer

Responsibilities

• Partner with customers to design scalable data architectures using Databricks technology and services.
• Drive complex technical discussions and communicate the value of the Databricks platform throughout the sales lifecycle.
• Engage technical stakeholders—including architects, engineers, and operations teams—as a trusted advisor.
• Develop account strategies with Sales and cross-functional partners to grow platform usage.
• Establish Databricks Lakehouse architecture as customers’ standard data architecture through technical account planning.
• Build and present reference architectures and demo applications for prospects.
• Consult on big data architectures, data engineering pipelines, and data science and machine learning projects.
• Prove Databricks technology for strategic customer projects and validate integrations with cloud services and third-party applications.
• Promote Databricks open-source projects, including Spark, Delta Lake, MLflow, and Koalas, through meetups, conferences, and webinars.
• Travel to customers in the region up to 30% of the time.

Requirements

• 4+ years of experience in customer-facing pre-sales, technical architecture, or consulting.
• Expertise in at least one of the following areas: big data engineering; data warehousing and ETL; data science and machine learning; or data applications.
• Ability to translate business needs into technology solutions and establish stakeholder buy-in.
• Experience designing, architecting, presenting, and managing delivery of production data systems.
• Fluency in SQL and database technology.
• Debugging and development experience in Python, Scala, Java, or R.

Nice-to-haves

• Experience building solutions with AWS, Azure, or Google Cloud.
• Degree in a quantitative discipline such as Computer Science, Applied Mathematics, or Operations Research.

Compensation and Benefits

• Comprehensive benefits and perks are offered, with details varying by region.