Solution Architect- Data engineer

We’re building the future of AI-powered data infrastructure—helping companies reimagine how they interact with their data warehouses.

We’re looking for a Solution Architect with a strong background in data engineering to join our founding team and work directly with our design partners to design and deliver scalable, AI-driven data solutions using our emerging platform.

This is a hybrid role combining technical architecture, solution design, and customer collaboration. You’ll help enterprises modernize their data environments while influencing the evolution of our product—laying the foundation for scalable, intelligent data experiences.

What You’ll Do

• Partner with future customers and design partners to architect and implement end-to-end data solutions using our SaaS platform.
• Translate customer requirements, pain points, and workflows into scalable data architectures and actionable insights for the product and engineering teams.
• Lead solution design sessions, proofs-of-concept, and pilot implementations across modern data stacks (Snowflake, dbt, BigQuery, Redshift, Databricks, etc.).
• Collaborate closely with engineering, data science, and product teams to ensure customer implementations shape the platform’s roadmap.
• Develop technical content, solution templates, architecture diagrams, and best-practice guides to scale customer success.
• Act as the primary technical point of contact for enterprise customers—bridging technical depth with business value.
  
  

• 8+ years of experience in data engineering.
• Strong technical expertise across modern data platforms (e.g., Snowflake, BigQuery, Databricks, dbt, Airflow).
• Proven experience designing and deploying data pipelines, integrations, and architectures in cloud environments (AWS, GCP, or Azure).
• Deep understanding of data modeling, transformation, and orchestration frameworks.
• Ability to translate complex data problems into scalable, customer-centric solutions.
• Excellent communication skills—able to interface confidently with both technical and business stakeholders.
• Hands-on, builder mindset- comfortable working in ambiguous, fast-paced startup environments.
• Experience leading customer-facing solution delivery or architecture engagements in global environments.
• Fluent English—capable of maintaining ongoing communication with enterprise clients.
  
  

• Experience with AI/LLM-based systems, semantic layers, or conversational data interfaces.
• Familiarity with enterprise SaaS integration patterns (SSO, APIs, RBAC, metadata management).
• Prior experience at an early-stage startup, especially in data or infrastructure domains.