We are building a world where analytics fuel the applications that drive business forward. Sisense is the premier AI-powered embedded analytics platform that empowers product and development teams to build accessible, data-driven insights into every product experience. With over 20 years of experience powering analytics in customer-facing products, we provide the governed distribution layer for product AI, allowing our customers to ground AI in their approved metrics, context, and access rules, then deliver it into the workflows their users already rely on.
From startups to the world's largest enterprises, Sisense turns data into a significant competitive advantage, accelerating product innovation and driving real business value.
The Role
As a Senior Presales Engineer, you will be a key technical partner to our Account Executives across the EMEA region, proving the value of Sisense throughout the sales cycle. You will lead technical discovery, design and deliver compelling proofs of concept (PoCs), and act as a trusted advisor to technical and business stakeholders evaluating our AI-powered embedded analytics platform.
This is a high-impact, customer-facing role combining deep technical expertise with strong business acumen to drive successful sales outcomes.
Work Schedule: Monday – Friday (aligning with global markets)
Key Responsibilities
Partner closely with Account Executives throughout the deal cycle to demonstrate the technical value and strategic ROI of Sisense.
Lead technical and business-focused discovery sessions to qualify opportunities, uncover customer pain points, and scope solution architecture.
Build, own, and deliver high-quality Proofs of Concept (PoCs) and technical demonstrations using the Sisense platform, including data modeling, dashboards, embedding via React/JS SDKs, and REST APIs.
Collaborate with internal cross-functional teams (Customer Success, Professional Services, Product, and Engineering) to ensure smooth deal progression and seamless post-sales handoffs.
Contribute to internal knowledge sharing, best practice documentation, and technical enablement across the global Sales Engineering team.
Stay abreast of trends in data engineering, embedded analytics, cloud architectures, and AI/LLM technology to provide strategic guidance.
Essential Qualifications & Skills
Demonstrated track record in a customer-facing technical pre-sales role (Sales Engineering, Solution Architecture, or Technical Consulting) supporting complex SaaS deal cycles.
Strong ability to communicate complex technical concepts clearly and persuasively to both developer teams and C-level executive stakeholders.
Hands-on expertise with SQL and modern data platforms (e.g., Snowflake, BigQuery, Databricks) and data architecture concepts.
Proficiency in JavaScript or modern web development frameworks (React, Angular, Vue), with practical exposure to application embedding and API integrations.
Solid understanding of business intelligence, analytics platforms, and cloud SaaS infrastructure.
Self-starter mindset with the ability to manage multiple live opportunities independently while knowing when to leverage internal expertise.
Fluency in English (written and spoken); additional European languages are a plus.
Desirable
Hands-on experience with Python or server-side development languages.
Background in embedded analytics, generative AI/ML architectures, or developer platform SDKs.
Familiarity with value-based selling methodologies (e.g., MEDDPICC, Challenger).
How You’ll Ramp (30-60-90 Day Success Criteria)
Day 30: Gain a comprehensive technical understanding of Sisense’s core capabilities and unique value proposition. Shadow live demos and customer discovery sessions. Begin demonstrating product features internally.
Day 60: Participate in the active demo pool, assist Account Executives on live deals, and actively partner on 4–5 active sales opportunities. Deliver tailored PoC scopes for prospects.
Day 90: Fully own Presales strategies and technical relationships within your assigned pipeline. Establish best practices for trial workflows and contribute to internal SE initiatives.
