Manager, Sales Engineering Specialists

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

Fivetran is building data pipelines to power the modern data stack for thousands of companies.

We’re looking for a Manager Sales Engineering Specialists to oversee our data platform Specialists functions. In this role, you will work alongside global Sales Engineering leadership to leverage a team of technical experts to accelerate our most complex enterprise deals, drive customer adoption after the sale, and improve the efficiency of the Sales Engineering motion at large. As customers build toward AI and agentic workloads, you will keep your team ahead of what those workloads demand of the data platform.

You will need a deep understanding of how modern data movement and transformation platforms like ours are architected, including the AI use cases built on top of them, and a keen ability to lead a team of highly specialized resources. You will be tasked with developing and retaining experienced, high-performing talent who can speak the language of enterprise architects, data engineers, and data platform owners, and with hiring where the team needs to grow.

This is a full-time position based in the US.

Technologies You’ll Use

Fivetran, dbt, Enterprise databases and applications (including SAP), cloud data warehouses and lakehouses (Snowflake, BigQuery, Databricks), open table formats (Apache Iceberg), dbt, SQL, reverse ETL, AI and agent tooling, AWS, GCP, Azure

What You’ll Do

• Lead a team of tenured experts across our data platform specialties to act as technical liaisons between Sales Engineering, Sales, Product, and Engineering.

• Support Global Sales teams by proactively embedding specialist functions to remove technical blockers in complex enterprise deals and in customer adoption after the sale.

• Implement strategies to maximize deal velocity and customer adoption by streamlining how specialists are engaged, prioritized, and measured.

• Execute hands-on tasks when needed, including architecture reviews, critical customer calls, or complex proofs of value.

• Ensure the team provides timely, strategic, and accurate guidance during technical evaluations and customer escalations.

• Build strong working relationships with strategic internal partners, including Product, Engineering, and other sales teams.

• Coach team members to maximize performance and efficiency, and prepare them for future roles.

• Ensure the team shares specialist knowledge across the field through enablement and documentation.

• Keep the team current on how AI and agentic workloads change customer requirements, and turn that into field guidance.

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