Solutions Architect - Digital Native Business, Strategic

<p>While candidates in the listed location(s) are encouraged for this role, candidates in other US locations will be considered. #LI-REMOTE</p> <p>As a Solutions Architect on the Digital Natives team, you will work with the leading data engineering, data science ML teams in the market to push the boundaries of what big data architectures are capable of. </p> <p>Reporting to the Field Engineering Manager, you will collaborate with strategic customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.</p> <p>We are looking for high technical aptitude individuals with a deep sense of ownership and a desire to help customers ship solutions at production scale. Ideal candidates are deeply curious, capable of operating with confidence in ambiguous situations, and are extremely adaptable. </p> <p><strong>The impact you will have:</strong></p> <ul> <li>You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.</li> <li>Drive technical discovery and solution design, focusing on winning competitive deals and accelerating time-to-value in strategic accounts.</li> <li>Continuously research learn new technologies and their implementations on Databricks</li> <li>Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications</li> <li>Collaborate with your fellow Solutions Architects, using your skills to support each other and our customers</li> <li>Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.</li> <li>Work closely with account executives to create and execute account penetration strategies, focusing on winning technical decision-makers and building new customer champions.</li> <li>Build trusted advisor relationships with senior and executive stakeholders by articulating the business value of Databricks in clear, outcomes-driven terms.<br><br></li> </ul> <p><strong>What we look for:</strong></p> <ul> <li>5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role</li> <li>Experience building distributed data systems</li> <li>Comfortable programming in, and debugging, Python and SQL</li> <li>Have built solutions with public cloud providers such as AWS, Azure, or GCP</li> <li>Expertise in one of the following:</li> <ul> <li>Data Engineering technologies (Ex: Spark, Hadoop, Kafka)</li> <li>Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)</li> </ul> <li>Strong executive presence with the ability to influence C/VP-level stakeholders and align technical solutions to strategic business priorities.</li> <li>Available to travel to customers in your region</li> <li>[Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)</li> <li>Nice to have: Databricks Certification<br><br></li> </ul> <p>NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply. We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.</p> <p data-renderer-start-pos="1648"><br><br></p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p> </p> <p><strong>Pay Range Transparency</strong></p> <p><span style="font-weight: 400; font-size: 14px;">Databricks is committed to fair and equitable compensation practices. The pay range(s) ... (truncated, view full listing at source)