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While candidates in the listed location(s) in Colorado, are encouraged for this role, candidates in other locations will be considered.
Solutions Architects at Databricks lead the adoption of the Databricks Unified Analytics Platform. As a member of our team, you will sharpen your skills on open-source projects such as Apache Spark™, MLflow, and Delta Lake to advocate the Lakehouse paradigm on public cloud providers. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this customer-facing role, you will identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through implementations to deliver strategic business value. You will partner with the sales team to build relationships with our customers and establish yourself as a trusted advisor.
Databricks' culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating in our subject matter expert groups. In this role, you will report to the Solutions Architect Leader supporting the specific business segment.
If you are a technologist interested in Data and AI, and enjoy prototyping solutions for customers, this role is for you.
The impact you will have: - Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks
- Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
- Build and present reference architectures, technical guides, and demo applications for customers
- Provide escalated support for critical customer operational issues
- Become an expert in, and evangelize Databricks driven open-source projects (Apache Spark™, Delta Lake, MLflow, Koalas) across developer communities through meetups, conferences, and webinars
- Use your strengths to help your fellow SA's, and drive cross-functional relationships across the company
- Travel to customers up to 30%
What we look for:Solution Architects are customer-facing. You'll need to be comfortable communicating ideas to various audiences through presentations, whiteboarding, architecture discussions, and platform demonstrations.
- 4+ years in a customer-facing pre-sales, technical architecture, or consulting role
- Experience designing and architecting distributed data systems
- Comfortable programming in and debugging at least one of Python, Scala, Java, SQL, or R
- Have built solutions with public cloud providers, such as AWS, Azure, or GCP
- Experience in at least one of the following:
- Data Engineering technologies (e.g., Spark, Hadoop, Kafka)
- Data Warehousing (e.g., SQL, OLTP/OLAP/DSS)
- Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)
- [Preferred] Degree in a quantitative discipline (e.g., Computer Science, Applied Mathematics, Operations Research, etc.)
- Nice to have: Databricks Certification
#CMEG
Pay Range TransparencyDatabricks 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 here.
Zone 3 Pay Range
$180,000-$247,500 USD
BenefitsAt Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
