Job Title: Founding Enterprise Solutions Architect – Data Tools & Infrastructure

Company: Row64

Location: Remote

About Us

Row64 is an early-stage, high-growth startup building the future of real-time data analytics and visualization. Modern data teams trust our platform to unlock insights, streamline operations, and power better decisions. We're backed by top-tier investors and led by a team of seasoned operators from the forefront of the data tooling and cloud ecosystem.

We're on a mission to empower users with the next generation of intuitive, scalable, and powerful data tools. We’re looking for an exceptional, hands-on Founding Enterprise Solutions Architect to help us bring our vision to more of the world’s most forward-thinking companies.

About the Role

We’re hiring a Founding Enterprise Solutions Architect to play a critical role in the success of our largest customers. In this highly visible and technically challenging position, you’ll act as a trusted advisor—guiding clients through our platform's architecture, integration, and optimization within their complex data environments.  You will bring our modern data science toolset to solve our clients’ challenges.

You’ll bring deep technical knowledge, strong communication skills, and a customer-first mindset to help enterprises fully realize the value of our solutions.

What You’ll Do

• Solution Design: Partner with enterprise customers to understand their data architecture and design scalable, high-impact solutions using our platform.
• Hands-On Integration: Guide technical onboarding and implementation efforts, working closely with customer engineering teams to ensure successful deployments.
• Technical Leadership: Serve as a subject matter expert in our products and the broader data ecosystem (e.g., data pipelines, storage, cloud infrastructure).
• Problem Solving: Proactively identify and troubleshoot issues across complex environments, coordinating with internal teams as needed.
• Enablement: Deliver onboarding workshops, technical training, and architecture reviews that drive product adoption and customer confidence.
• Documentation & Best Practices: Create and maintain internal and customer-facing documentation that accelerates implementation and reduces friction.
• Customer Advocacy: Gather customer feedback and collaborate with Product and Engineering to improve functionality, performance, and usability.
• Cross-functional collaboration: Work closely with Sales, Support, Product, and Customer Success to deliver a seamless and impactful customer experience.

What You Bring

• 5+ years in a customer-facing technical role such as Solutions Architect, Sales Engineer, or Technical Account Manager—ideally in the data tooling, cloud infrastructure, or enterprise SaaS space.
• Deep familiarity with data science, modern data architectures, including data warehouses, lakehouses, and pipeline orchestration tools (e.g., Snowflake, dbt, Airflow, Kafka, power bi, tableau).
• Strong technical foundation with experience in Python, SQL, and/or cloud infrastructure (AWS, GCP, Azure).
• Exceptional communication and presentation skills—you can translate complex concepts for technical and non-technical audiences.
• Proven ability to build trusted relationships with enterprise customers and navigate complex organizational structures.
• Experience working in high-growth startup environments is a strong plus.
• A collaborative mindset and bias toward action—you thrive in fast-paced, cross-functional teams.

Why You’ll Love It Here

• High-impact role at a fast-growing startup in a booming space.
• Remote-first culture with flexible working hours.
• Competitive compensation and meaningful equity.
• Collaborative, low-ego team that values learning, innovation, and excellence.
• Access to cutting-edge tools and technologies in the modern data stack.
• Opportunities to influence product direction and shape the future of enterprise data infrastructure.

Join Us

We'd love to hear from you if you're excited about working with customers to solve complex technical problems and enabling data-driven transformation at scale.