FEQ327R400
Mission
Solutions Architects at Confidential (Registered Users Only) lead the growth of the Confidential (Registered Users Only) Unified Analytics Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science and machine learning. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark, MLflow, and Delta Lake. This is a customer-facing role, where you will work with customers, your teammates, the product team, and our post-sales teams, to identify use cases for Confidential (Registered Users Only), develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish value. In that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will report to the Field Engineering Manager for the team.
The impact you will have:
- Partner with the sales team to help customers understand how Confidential (Registered Users Only) can help solve their business problems
- Provide technical leadership for customers to evaluate and adopt Confidential (Registered Users Only)
- 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 references architectures, how-tos, and demo applications for customers
- Become an expert in, and promote Confidential (Registered Users Only) inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars
- Travel to customers in your region
What we look for:
- 7+ 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
- Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
- Data Warehousing (Ex: SQL, OLTP/OLAP/DSS)
- Experience supporting Financial Services clients is a plus
- [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)