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.
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.
Fivetran and dbt are building the open data infrastructure that powers AI agents you can trust.
Fivetran is looking for a Senior R&D Software Engineer to join our fast-growing Fivetran AI team. Your data stack was built for humans — but agents are the new primary data consumers, and they have fundamentally different requirements. Agents can’t intuit context; it must be explicitly codified, governed, and traceable. We’re building the governed context layer that solves this problem: Agents Schema, an open standard for storing agent-ready context directly in the customer’s own data warehouse, and Context Builder, the managed service that keeps it filled and fresh.
This role goes well beyond standard engineering. You’ll research emerging techniques in the fast-moving AI landscape and bring real product and market understanding to decide which ideas are worth pursuing — and then you’ll take what you’ve learned and ship it as production software. We’re looking for a true generalist who is willing and able to wear whatever hat the moment calls for: prototyping a new retrieval technique one week, hardening a backend service the next, then doing SRE or QA work when the team needs it. Fivetran AI operates like a startup within Fivetran, and we need engineers who thrive on that range rather than staying in one lane.
Fivetran is the epitome of data-driven development — our engineering team is focused on building a world class product that:
Builds Infrastructure Agents Can Trust — join our mission to deliver the governed context layer that AI agents depend on: accurate semantic definitions, traceable lineage, data contracts, and auditable history baked in from the start.
Embraces Open Standards — help build portable, interoperable data infrastructure: Agents Schema, open formats (Iceberg, Delta Lake), MCP-native interfaces, and connector skills that work with any model and any compute.
Scales Without Breaking — work to make Fivetran AI efficient at agent scale, where unit costs deflate as volume grows and context retrieval is fast, accurate, and cost-controlled.
We emphasize using no-nonsense tools and take great pride in the simplicity and effectiveness of the systems we build. Our back-end is built on Java, Python, Postgres, and Kubernetes, and our front-end is built on React and TypeScript.
This is a full-time hybrid position based out of our New York, NY office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team.
Technologies You’ll Use
Python, Java, SQL, dbt, LLMs (Claude, ChatGPT, Gemini), vector databases, BigQuery / Snowflake / Databricks, MCP protocol, React, TypeScript, Kubernetes