Staff Solutions Engineer

From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven.

About Us

Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.

About the Role

We’re looking to hire a Solutions Engineer, Enterprise to join our Field Engineering team. As a Solutions Architect, you will be a trusted technical advisor to some of our largest and most strategic customers, helping them evaluate, adopt, and expand their use of dbt.

You’ll partner closely with Sales to understand customers’ technical and business priorities, design solutions using the dbt platform, and demonstrate measurable value throughout the evaluation process. You’ll work across the customer lifecycle—from technical discovery and evaluation through adoption and expansion—while partnering with Product, Engineering, and our technology partners to bring customer needs back into the business.

This is a full-time position based in New York City.

Technologies You’ll Use

SQL, dbt, cloud data warehouses and lakehouses including Snowflake, Databricks, and BigQuery, AWS, Azure, and GCP, modern data integration and orchestration technologies, and AI-assisted productivity tools.

What You’ll Do

Lead technical discovery with enterprise customers, connecting technical requirements to business outcomes and measurable success criteria

Design enterprise-grade data transformation and analytics architectures using dbt

Partner with Sales to communicate the technical and business value of the dbt platform

Lead customer evaluations and technical validation, including trials and proof-of-value engagements when appropriate

Build trusted relationships with technical practitioners, data leaders, and executive stakeholders

Guide customers through technical architecture, security, governance, and deployment considerations

Partner across the customer lifecycle to support successful adoption and identify opportunities for expansion

Bring customer and field insights to Product and Engineering to help influence product strategy and roadmap

Build strong relationships with technology and consulting partners, including Snowflake, Databricks, AWS, and other members of the modern data ecosystem

Contribute technical expertise, reusable best practices, and thought leadership to the broader Field Engineering organization and dbt community

Skills We’re Looking For

4+ years of experience in sales engineering, solutions architecture, consulting, or a similar customer-facing technical role within data, analytics, or BI

Strong technical foundation in SQL, data transformation, ETL/ELT, and data modeling

Strong understanding of modern cloud data warehouse, lake house, and analytics architectures