At Confluent, we’re creating a category that transforms how every company manages and streams data. Have you ever found a new favorite series on Netflix, picked up groceries curbside at Walmart, or paid for something using Square? That’s Confluent in action—giving our customers instant access to massive amounts of real-time data, enabling them to thrive in an ever-changing digital world. As one of the fastest-growing enterprise companies in history, and with Fortune 100 customers across major industries, we have a tremendous opportunity in front of us. We also have experience on our side. Our leaders have taken companies of our size to major success before and include some of the original creators of Apache Kafka®.
We’re looking for self-motivated team members who crave a challenge and feel energized to roll up their sleeves and help realize Confluent’s unlimited potential. Chart your own path and take healthy risks with the backing and support of our #OneTeam culture. Be part of inclusive initiatives like Employee Resource Groups and development programs, and take advantage of benefits that support our diverse global teams. Grow as we grow—whether you’re just starting out or managing a large team, you’ll be amazed at the magnitude of your impact.
Confluent sales engineers drive the technical evaluation stage of the overall sales process, making them critical drivers of customer success as realtime data streams become more and more important in the modern enterprise. In this role you will be the key technical advisor to the sales team, work very closely with the product management and engineering teams, and serve as a vital product advocate in front of prospects, customers, and the wider Kafka and Big Data communities.
You will be a key technical advisor to Confluent customers as they undertake technical design and development of their end-to-end solution, be conversant with the current state and future roadmap of Kafka in open source, and be able to identify known issues and inform them of upcoming fixes or workarounds. You’ll also be responsible for clear articulation of Confluent’s technical and product positioning to a wide variety of business and technical stakeholders, and for forging strong relationships with them throughout the sales cycle and beyond.
What we're looking for:
Experience with technical sales of distributed systems, infrastructure software like databases, message queues, SaaS, or Big Data products
Exceptional presentation and communications capabilities. Confidence presenting to a highly skilled and experienced audience, including enterprise architects and C-level executives
Clear, consistent demonstration of self-starter behavior and a desire to tackle hard technical problems
Bachelor’s level degree in Computer Science or relevant experience
Proficiency in Java or Python with experience developing ETL applications
What gives you an edge:
Previous experience building solutions with Apache Kafka
Understanding of systems operations concepts (disk, network, operating systems, etc)
Experience building and operating large-scale systems
Come As You Are
At Confluent, equality is a core tenet of our culture. We are committed to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. The more diverse we are, the richer our community and the broader our impact.
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Founded by the team that built Apache Kafka®, Confluent builds a streaming platform
that enables companies to easily access data as real-time streams
Every byte of data has a story to tell, something of significance that will inform the next thing to be done. In a data-driven enterprise, how we move our data becomes nearly as important as the data itself. With greater speed and agility, data’s value increases exponentially.
From its very early days, we have open-sourced Apache Kafka™ and have led it to impressive industry-wide adoption across several thousand companies. Now we are focusing on building a streaming platform to help other companies get easy access to enterprise data as real-time streams.