Pre-Sales Engineer/Solutions Architect

San Jose, CA /
Sales /
Who we are: 

Here at Xcalar, we do things differently and trust us, that’s a good thing. Not only do we build tools that make data useful and simple, but we also build them to be beautiful. We are a team of creative individuals that come together and push ourselves beyond our comfort zone—from unprecedented technology to user experience, from interaction design to scalability, from machine learning to data virtualization, we come together to move mountains to achieve what people might believe is the impossible!
Xcalar, backed by top tier VCs like Khosla Ventures, Merus Capital and other tech luminaries including Vinod Khosla, Andreas Bechtolsheim, and Diane Greene.
Who are you:
Xcalar is pushing the limits of technology to help people discover deep meaningful insights from data. Our mission is to become the de facto standard for next generation big data processing and analytics engines.
Due to our continued growth, we are looking to hire a Sales Engineer.
As a core member of this team, you will build killer demos and case studies, and help develop a game-changing product that will revolutionize how big data is parsed, processed, and visualized. You will represent Xcalar throughout the sales process, work with clients to architect solutions, and contribute to the core engineering workstream extending our product that enables customers to discover deep insights from big data.
You should have a solid SQL, analytics, infrastructure, and Python background. Machine learning and JavaScript experience is a big plus. The candidate must be able to carry on deep discussions with the customer's technical experts, as well as high-level business talks with senior executives.


    • Define, analyze, and design technical solutions to the customer’s business problems
    • Help extend Xcalar’s product to meet the customer’s needs and advance the company's sales efforts
    • Build killer demos and case studies that demonstrate how Xcalar can be used to push technology boundaries to the limit, achieving what was not possible
    • Develop and maintain deep technical expertise in the Xcalar product portfolio
    • Technically support Xcalar’s fast-growing sales team, who take on the largest industry incumbents
    • Work with Xcalar’s world class engineering team, who design and build high performance analytics systems, tools, and services
    • Work on UI design and product definition that leads, influences, and adds key value to the Xcalar product line and collaborate with frontend and backend engineers
    • Help build and bring to market the next generation big data analytics platform that interactively explores a trillion rows of data using relational operations, algorithmic modeling, and machine learning

Minimum requirements

    • B.S./M.S. in Computer Science, Mathematics, or other technical major
    • Minimum of 6 years+ experience with engineering enterprise solutions
    • Experience with BI tools (e.g., Qlik, Tableau, Looker) is a plus
    • Deep understanding of SQL and relational databases
    • Understanding of big data, analytics, data science, machine learning, data preparation, scale-out computing, data warehousing, and business intelligence
    • Experience with MS Azure, Google Cloud, AWS, Hadoop, Spark, and Linux
    • Experience with Python
    • Great communication skills, being able to speak to both technical and business counterparts on the client side and explain technology and solutions architecture
    • Some travel required
Xcalar is committed to diversity in its workforce and is proud to be an equal opportunity employer. Xcalar considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, or any other legally protected class.
Xcalar reserves the right of ownership for all unsolicited resumes submitted for this requisition and is not responsible for any fees associated with unsolicited resumes.