Sr. Solutions Engineer - AI Natives Business

As a Sr. Solutions Engineer on the AI native team supporting the Digital Natives business, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world. Reporting to the Field Engineering Manager, you will collaborate with 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. The impact you will have: Partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems. 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. Collaborate with your fellow Solutions Architects, using your skills to support each other and our users. Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community. What we look for: 3+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role Experience building distributed data systems Comfortable programming in and debugging Python and SQL Have built solutions with public cloud providers such as AWS, Azure, or GCP Expertise in one of the following: Data Engineering technologies (e.g., Spark, Hadoop, Kafka) Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, PyTorch, Tensorflow) Available to travel to customers in your region Desired: Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research) Nice to have: Databricks Certification Location: Remote (Pacific Time preferred; Mountain Time considered). 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. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page.

$152,300 — $209,450 USD

Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone. #J-18808-Ljbffr Cacheflow