As a Senior Solutions Engineer at KNIME, you are a strategic technical partner to prospects and customers throughout the sales lifecycle. You combine curiosity, technical depth, business acumen, and strong communication skills to help organizations understand how KNIME can solve meaningful data, analytics, automation, and AI challenges. Working closely with the sales team, you own the technical strategy for assigned opportunities and accounts — from discovery and solution design through demonstration, technical validation, and expansion. You are expected to understand the customer’s business problem before proposing a solution, translate complex requirements into a compelling KNIME architecture, and build confidence across business, data, IT, security, and executive stakeholders. Senior Solutions Engineers are hands-on. You should be comfortable conducting discovery, building and delivering demonstrations, designing solutions, and leading technical evaluations independently. You will also engage specialist resources when deeper product, architecture, or domain expertise can accelerate or strengthen the opportunity. ### Lead Technical Discovery and Sales Strategy Lead thoughtful, structured discovery to understand business priorities, current workflows, data environments, stakeholders, constraints, and desired outcomes. Translate customer challenges into clearly defined use cases, technical requirements, and measurable success criteria. Develop the technical strategy for opportunities in partnership with the account team, including stakeholder engagement, competitive differentiation, evaluation strategy, and technical win criteria. Identify and develop technical champions while building trusted relationships with data, analytics, AI, IT, security, and business stakeholders. Communicate effectively across audiences, from hands-on practitioners to senior executives. ### Design and Demonstrate Solutions Map customer requirements to KNIME capabilities across data access, transformation, analytics, automation, AI, application delivery, governance, and deployment. Build and deliver compelling demonstrations that reflect the customer’s environment, priorities, and business outcomes rather than relying on generic feature presentations. Use workshops, solution design sessions, prototypes, and proofs of concept when they are the best way to advance customer confidence and decision-making. Define clear objectives and exit criteria for technical evaluations and keep evaluations focused on the capabilities required to make a buying decision. Translate technical capabilities into measurable outcomes such as productivity gains, reduced operational cost, faster time to insight, improved governance, and reduced risk. ### Guide Enterprise Architecture and Technical Validation Help customers determine how KNIME fits into their broader data, analytics, and AI architecture. Advise customers on SaaS and self-managed deployment models based on security, governance, scale, integration, and operational requirements. Navigate enterprise technical topics including cloud architecture, identity and access management, data connectivity, APIs, authentication, security, governance, and deployment. Help customers evaluate modern AI and GenAI use cases, including responsible AI adoption, model and provider integration, workflow orchestration, governance, and operationalization. Partner with security, architecture, product, and other specialists when deeper expertise is required. ### Grow the Customer Relationship Look beyond the initial use case to identify opportunities for broader adoption across teams, departments, workflows, and business processes. Surface new use cases and technical expansion opportunities to the account and customer success teams. Help customers envision how successful individual workflows can evolve into repeatable, governed enterprise capabilities. Ensure strong technical handoffs following a sale so Customer Success, Professional Services, Support, and other teams understand the customer’s objectives, architecture, success criteria, and commitments. Identify technical risk that could affect adoption, expansion, or renewal and partner with the appropriate teams to address it. ### Contribute to a High-Performing Solutions Organization Maintain accurate technical context, solution strategy, evaluation status, and technical win criteria in Salesforce. Bring customer, competitive, and market insights back to Product, Engineering, Marketing, and Solutions leadership. Create reusable demonstrations, discovery approaches, architectures, workflows, and field assets that increase the effectiveness of the broader team. Share expertise with peers and contribute to a culture of learning, experimentation, and continuous improvement. Stay current on developments in analytics, data engineering, AI, GenAI, cloud architecture, and the broader enterprise data ecosystem. 5+ years of experience in Solutions Engineering, Sales Engineering, Pre-Sales, technical consulting, data consulting, or a comparable customer-facing technical role in enterprise software. Demonstrated ability to lead discovery, design solutions, deliver compelling demonstrations, and guide complex technical evaluations. Strong understanding of modern data and analytics concepts, including data integration, transformation, ETL/ELT, analytics, automation, machine learning, and AI. Familiarity with SQL and at least one common analytical or programming environment such as Python or R. Working knowledge of enterprise SaaS and cloud architecture, including APIs, authentication, SSO/identity, security, governance, and integration patterns. Growing fluency with modern AI and GenAI architectures, including LLMs, AI providers, retrieval and data access patterns, agents, governance, and responsible AI considerations. Strong business acumen and the ability to connect technology decisions to business outcomes. Excellent presentation, storytelling, workshop facilitation, and executive communication skills. Ability to navigate complex, multi-stakeholder enterprise buying processes while remaining focused on the customer’s desired outcomes. Comfort operating with autonomy, prioritizing across multiple opportunities, and collaborating across a matrixed organization. Preferred Experience -------------------- Hands-on experience with KNIME Analytics Platform or KNIME Business Hub. Experience with adjacent data and analytics platforms such as Alteryx, Dataiku, Databricks, Snowflake, or similar enterprise technologies. Experience selling or supporting enterprise SaaS, analytics, data, automation, or AI platforms. Experience working with cloud environments such as AWS, Azure, or Google Cloud. Experience supporting enterprise security, architecture, or AI-governance conversations. Familiarity with structured discovery, qualification, and value-selling methodologies. Experience working closely with Account Executives, Customer Success, Product, and Professional Services teams in a SaaS organization. Success in this role is measured not simply by technical activity, but by your ability to create customer confidence, establish clear technical value, remove risk from the buying process, and contribute to sustainable revenue growth. 401(k) matching to support your long-term financial goals Flexible working hours and a remote-friendly working environment Learning & development support , including training, online learning resources, and opportunities to attend conferences Employee referral program Regular team events and opportunities to connect with colleagues across our international organization