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 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

What You’ll Do

• Research emerging techniques in retrieval, reasoning, and agentic AI, and evaluate what’s actually relevant to Fivetran AI’s roadmap
• Prototype new ideas quickly, then take the ones that prove out and turn them into shipped, production-grade features
• Build and maintain both back-end and front-end systems for the Fivetran AI product — from Agents Schema pipelines to the Context Catalog UI
• Contribute to the AISQL capability: natural language to SQL grounded in dbt metric definitions, executed natively against the warehouse
• Take ownership of production reliability: on-call rotation, incident response, and SRE work to keep the platform trustworthy at scale
• Write and maintain tests, and do hands-on QA to catch issues before customers do
• Use coding agents to automate the repetitive parts of the job, freeing up time for the research and design work that needs a human
• Partner with product and design, bringing your own understanding of the AI tooling market to shape what gets built next
• Develop software designs and contribute to the technical roadmap for the Fivetran AI platform
• Contribute to hiring by participating in the interview process

Skills We’re Looking For

• 5+ years of programming experience across Python and/or Java, with the ability to move fluidly between back-end and front-end work
• Considered a trusted expert in your subject area, capable of executing complex, ambiguous tasks with minimal hand-holding
• Comfortable reading AI/ML research and turning promising findings into working prototypes
• Strong product and market awareness — able to judge which emerging techniques are worth building versus which are hype
• Experience with SQL and data warehouses (BigQuery, Snowflake, Databricks, or similar)
• Genuine willingness to work across the full stack: research, backend, frontend, SRE, and QA, as the team’s needs demand
• Writes well-structured, performant code and can dive into unfamiliar codebases to suggest improvements
• Experience using coding agents or similar AI tooling to speed up day-to-day engineering work
• Analytical mindset to identify gaps in existing systems and design practical, pragmatic improvements
• Thrives in a startup-like environment with shifting priorities and a high degree of ownership

Bonus Skills

• Experience with LLM-powered applications — RAG pipelines, embeddings, evaluation frameworks, or agent frameworks
• Familiarity with semantic layers — dbt, LookML, Sigma, or similar
• Experience with the MCP (Model Context Protocol) ecosystem or building AI agent integrations
• Background in site reliability engineering — monitoring, alerting, incident response
• Experience in data processing (ETL, ELT) and/or building data connectors
• Experienced working in a cloud environment utilizing AWS, GCP, Kubernetes, or Docker
• Contributions to open source AI or data projects

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