Key Responsibilities
Win the technical case. Partner with our sales organization to demonstrate our value to prospects and drive adoption. You'll own the "technical win" on every opportunity you touch.
Get prospects to production. Provide technical review and recommendations for deploying us in production environments, and help prospects set up, tune, and benchmark the database during Proof-of-Concept phases.
Build and document solutions. Design our solutions and capture them in clear documentation – including integration guides and benchmarks of third-party tools working alongside our products.
Teach the technology. Develop training materials for our customers, and create and deliver training that helps users get the most out of the platform.
Connect the dots. Collaborate closely with other Solution Architects, and act as the bridge between customers and our product management and engineering teams – carrying real-world feedback back to the people building the product.
Pre-Sales / SA experience. 4+ years in a Pre-Sales or Solution Architect role, where you've owned the technical relationship with prospects and earned their trust.
Deep Linux fluency. Excellent working knowledge of Linux operating systems – you're comfortable operating, troubleshooting, and tuning in a Linux environment.
Startup instincts. Experience working in a startup environment, where ambiguity is normal, ownership is high, and moving fast matters.
A feel for selling services. Experience selling DBaaS or other service-oriented products, with an understanding of how technical value translates into a buying decision.
Hands-on NoSQL expertise. 2+ years deploying and managing NoSQL databases (including data modeling and deploying applications on systems like Cassandra/DataStax, MongoDB, or Redis).
Coding ability. A solid command of modern scripting languages (e.g. Python, Node.js) and/or popular programming languages (e.g. C/C++, Java, C#) – enough to build, integrate, and demonstrate, not just discuss.
Big-data ecosystem exposure. Hands-on experience with tools like Spark, Kafka, time-series databases, and graph databases.
A relevant foundation. An undergraduate degree in engineering, computer science, or a similar field.
Outstanding communication. Exceptional written and verbal skills – you can explain complex technical concepts clearly to engineers and executives alike.
