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.

Requirements:

Must-Haves

• 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.

Nice-to-Haves

• 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.