We are looking for a passionate, skilled, and experienced Sales Engineer / Solutions Architect to join Wherobots’ dynamic team in building the geospatial cloud database of the future, its cloud platform, and control plane. The Sales Engineer / Solutions Architect plays a crucial role in the success of our company by providing technical expertise and support to our clients during both the pre-sales and post-sales phases. You will be responsible for understanding the technical needs of customers, demonstrating how our products or services meet those needs, and ensuring a smooth transition from sales to implementation and support.
Key Responsibilities:
Pre-Sales:
Collaborate with the sales team to identify client needs and tailor technical solutions to meet those needs.
Prepare and deliver technical presentations, product demonstrations, and proposals to potential clients.
Act as a technical advisor to clients, addressing their inquiries and concerns with professionalism and expertise.
Assist in the development of RFPs, RFIs, and other technical documentation.
Stay updated on industry trends, competitor products, and emerging technologies to provide valuable insights to the sales team.
Post-Sales:
Work closely with clients to ensure a smooth transition from the sales phase to implementation, addressing technical challenges and concerns.
Provide training and technical support to clients to ensure they can effectively use our products or services.
Collaborate with the product development team to relay customer feedback and feature requests.
Troubleshoot and resolve technical issues, working in tandem with the customer support team.
Document client interactions, technical solutions, and best practices to improve future customer interactions.
Requirements:
Bachelor's degree in a related field (e.g., Computer Science, Engineering, related field or equivalent experience)
Minimum 5+ years experience in a pre-sales and post-sales technical support role.
Strong understanding of complete data analytics stack and workflow, from ETL to data platform design to BI and analytics tools
Excellent communication and presentation skills with the ability to articulate complex ideas and concepts to both technical and non-technical stakeholders.
Strong skills in databases, data warehouses, and data processing.
Problem-solving and analytical abilities.
Customer-focused with a commitment to client satisfaction.
Preferred Qualifications:
Experience and track record of success selling data and/or analytics software to enterprise customers; includes proven skills in identifying key stakeholders, winning value propositions and compelling events.
Data Science/AI experience across a variety of platforms
Extensive knowledge of and experience with large-scale database technology
Familiarity and experience with common BI and data exploration tools (e.g. Microstrategy, Business Objects, Tableau, etc).
Proven success at enterprise software start-ups
Wherobots offers competitive compensation, equity, and benefits.
Although we aim to establish a primary engineering presence in the San Francisco Bay Area, we provide flexibility and choice in the working arrangement for most roles, including remote and/or in-office roles. Please note that the base pay range is a guideline and for candidates who receive an offer, the base pay will vary based on factors such as work location, seniority, skills, and experience of the candidate.
Wherobots provides a competitive benefits package to all full-time employees, including 100% coverage of medical, dental, and vision insurance, access to a 401(k) plan, and unlimited PTO.
Wherobots was founded by the original creators of Apache Sedona to build the first fully managed, highly scalable geospatial cloud database and analytics platform: Wherobots Cloud. Geospatial, location-enabled, and satellite imagery data are quickly becoming a critical and valuable source of information and insights to a broad array of industries, from logistics and insurance to financial or climate tech companies. Wherobots helps those companies bring their geospatial data down to earth and drive value from it for their business and their customers through full-featured and scalable computation, querying analytics, and visualization capabilities.
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