Database Support Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Database Support Engineer based in the United States (East Coast, Remote). As a Database Support Engineer, you will play a key role in helping enterprise customers successfully deploy, optimize, and scale a next-generation AI-native database platform. You will guide customers throughout their post-sales journey, from onboarding and production deployment to ongoing adoption and technical optimization. Combining deep database expertise with a customer-centric mindset, you will troubleshoot complex technical challenges and help organizations unlock the full value of their data. You will also collaborate with sales teams on technical evaluations and proof-of-concept initiatives when needed. Working closely with product and engineering teams, you will translate customer feedback into actionable insights that drive continuous product improvement. This role offers the opportunity to contribute to the growing field of agentic AI while building trusted customer relationships in a fast-paced, innovative, and technically challenging environment.

Customer Onboarding and Deployment: Guide new customers through implementation and deployment, ensuring that solutions designed during the sales cycle are successfully delivered and operationalized in production environments. Customer Adoption and Expansion: Serve as the primary technical point of contact after the sale, supporting product adoption, resolving technical issues, and identifying opportunities to expand customer usage. Customer Relationship Management: Build trusted, long-term relationships with technical stakeholders, develop a deep understanding of their business objectives and technical constraints, and advocate for their needs internally. Technical Health and Optimization: Proactively assess customer environments, troubleshoot production issues, monitor technical health, and recommend architectural or configuration improvements as requirements evolve. Product and Engineering Collaboration: Share recurring customer challenges, technical feedback, and product improvement opportunities with product management and engineering teams to inform the platform roadmap. Pre-Sales and Proof-of-Concept Support: Assist sales teams with technical evaluations, proof-of-concept (PoC) design and execution, and customer demonstrations when additional pre-sales support is needed. Technical Documentation: Maintain detailed records of customer evaluations, use cases, technical challenges, PoC plans, and outcomes to improve internal processes and support product development. Cross-Functional Collaboration: Partner with sales teams to align technical discussions with business objectives, address customer objections, support deal progression, and contribute to revenue growth. Marketing and Thought Leadership: Represent the platform through webinars, industry conferences, user groups, technical blog posts, and other initiatives that showcase agentic AI use cases and best practices. Ownership and Continuous Improvement: Take responsibility for customer outcomes, build trust through transparent communication, exercise sound judgment, and contribute to a culture of innovation, accountability, and continuous learning. Requirements Professional Experience: At least 5 years of experience in pre-sales, post-sales, solutions engineering, technical consulting, or customer success engineering, ideally within database technologies, data analytics, or cloud infrastructure. Database and Analytics Expertise: Hands-on experience with online analytical processing (OLAP) workloads, query optimization, and data modeling techniques, including star and snowflake schemas. SQL Proficiency: Strong SQL skills and the ability to analyze queries, investigate performance issues, and support complex data-related use cases. Distributed Systems Knowledge: A solid understanding of distributed data processing systems, including their underlying principles, architecture, and performance considerations. Cloud Platform Experience: Familiarity with at least one major public cloud provider, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure. Technical Problem-Solving: Demonstrated ability to troubleshoot complex technical issues, support proof-of-concept initiatives, and adapt solutions to meet diverse customer requirements. Communication and Presentation Skills: Ability to translate complex technical concepts into clear, compelling explanations for a range of audiences, from engineers and technical decision-makers to C-level executives. Customer Success and Commercial Mindset: Experience supporting pre-sales and post-sales teams during technical evaluations, demonstrating technical value, overcoming objections, and contributing to customer retention, expansion, and revenue growth. Learning Agility and Curiosity: A proactive, inquisitive mindset with the motivation to master new technologies, understand an AI-native database platform, and tackle challenging technical problems. Candidates who demonstrate strong fundamentals and a willingness to grow are encouraged to apply, even if they do not meet every preferred skill. Preferred Qualifications: Familiarity with business intelligence tools such as Tableau or Looker, and experience with streaming data processing technologies such as Kafka or Redpanda. Working Style: Strong ownership, sound judgment, adaptability, and a collaborative approach, with a commitment to building trust, moving quickly without compromising quality, embracing AI-first practices, and raising standards without ego. Benefits Competitive Compensation: Annual base salary ranging from $150,000 to $200,000 , depending on experience, role scope, and interview results. Equity Compensation: An equity component that offers the opportunity to participate in the company's long-term growth. Comprehensive Benefits: Access to a full employee benefits package. Remote Flexibility: Work remotely from the United States, with a focus on the East Coast. Professional Development: Opportunities to deepen your expertise in distributed databases, cloud infrastructure, AI-native technologies, and agentic AI applications. Meaningful Technical Impact: Help enterprise customers solve complex data challenges while influencing product improvements and technical strategy. Cross-Functional Exposure: Collaborate with customer success, sales, product, and engineering teams in a dynamic, innovation-driven environment. Inclusive Workplace: Join a team committed to equal employment opportunities and a workplace that welcomes people from diverse backgrounds.