We are looking for an experienced Forward Deployed Data Architect — someone who has spent their career embedded directly with customers,defining, building and shipping data solutions hands-on, not just advising on them. You'll serve as the bridge between customer business challenges, modern data architectures, and RiverPool's product capabilities — working side-by-side with our customers' teams to design, build, and iterate on real analytics and data-platform solutions, while feeding what you learn directly back into our product.
This role requires a genuine data engineering and analytics background — real hands-on pipeline/platform/ analytics -building experience, not purely whiteboard-level architecture — combined with comfort working directly, in the field, with customer technical teams and stakeholders. As an early founding position, you will play a critical role in our entire business life cycle, from pre-sales and acquiring new customers, to onboard new clients and enable them in their day to day. Responsibilities
Forward-Deployed Delivery
Embed directly with our customers to map and fully understand the customer environment, ensuring full implementation of our platform, and fast value creation
Provide domain expertise guidance and hands-on implementation support throughout discovery, and adoption phases.
Act as a trusted, hands-on analytics partner to customer business teams, data engineers, analytics leaders, and executives alike.
Customer & Business Engagement
Lead customer discovery sessions to understand business objectives, data challenges, and technical requirements.
Translate complex business needs into clear product requirements, and work internally with our product and R&D to prioritize it.
Support strategic customer engagements, workshops, proofs-of-concept, and design partner programs.
Product & Platform Influence
Act as the voice of the customer within RiverPool.
Partner closely with Founders and Engineering teams to influence roadmap priorities.
Identify recurring customer requirements and translate them into scalable platform capabilities.
Requirements:
Must-Haves
8+ years of hands-on experience in Data Engineering, Analytics Engineering, or Data Architecture — genuine builder background, not purely advisory.
Proven track record building and deploying data analytics solutions directly embedded in enterprise customer environments
Deep expertise in modern data architectures, pipelines, and analytics ecosystems.
Hands-on technical ability: can build POCs, pipelines, and integrations directly.
Experience working directly with customers through discovery, implementation, and iteration.
Experience with AI, GenAI, LLM-powered applications, or agentic systems.
Strong communication skills.
Nice-to-Haves
Experience with: Snowflake, Databricks, dbt, BigQuery, Redshift, Azure Data Platform, Looker, Tableau, Power BI, Monte Carlo, Atlan, Alation.
Prior "Forward Deployed Engineer"- or enterprise pre-sales/solution-delivery background.
Experience in early-stage or venture-backed startups.
Willingness to travel or work on-site with customers as needed.