Senior Full Stack AI Engineer - Product Ops - Part-time

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 the Role

Fivetran is building data pipelines to power the modern data stack for thousands of companies. As we scale, we’re looking for a part-time Senior Full Stack AI Engineer to help unlock strategic insights, streamline systems, and develop intelligent, data-driven solutions that empower product managers and executives to make informed, faster decisions.

As a part-time Senior Full Stack AI Engineer, you’ll play critical role in helping Product Ops scale its impact across the company. You’ll design and implement solutions that make critical data accessible in real time, break down silos across tools like BigQuery, Looker, Heap, and Jira, and reduce operational friction. You’ll also be a key force behind developing AI-powered agents that automate the extraction of insights and simplify access to complex data for stakeholders at all levels.

This role is ideal for a hands-on builder who excels at the intersection of product, technology, and data — someone who can seamlessly transition from SQL to automation scripts to personalized AI agents without missing a beat.

This is a part-time (20-24 hours per week), hybrid position based out of our Oakland, CA 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

• Big Data: BigQuery (strong), SQL (strong), Firestore (Firebase)
• LLMs: Claude, GPT-4, and Gemini
• Languages: Python, JavaScript/Node.js
• Project Management, CRM & Support Systems: Jira, Zendesk, Salesforce, Gong
• Developer Platforms: Git, GitHub
• Analytics & BI: Heap, Looker, Sigma
• (Bonus) Frontend Frameworks: React, Angular, or Vue.js

What You’ll Do

• Be the technical backbone of Product Ops, leading the development of queries, tools, and dashboards that power the product org’s operations.
• Build highly performant and flexible SQL queries in BigQuery to extract and transform complex datasets that fuel key decision-making.
• Create ground up and maintain custom AI agents and internal tools to help Product Managers and Executives quickly access relevant data, draft compelling PRDs, synthesize customer feedback, and align with strategic goals and OKRs.
• Collaborate with the Analytics team to build self-service dashboards in Looker and other BI tools to answer recurring product questions and reduce dependency on manual analytics work.
• Develop end-to-end data pipelines and workflows that integrate across Jira, Heap, Zendesk, Salesforce, Gong, Aha!, and other solutions.
• Serve as a systems architect within Product Ops—identifying bottlenecks, unifying tooling strategies, and enabling cross-functional alignment through automation and smart data infrastructure.
• Partner closely with Engineering, Analytics, and GTM functions to ensure tooling and reporting solutions are deeply integrated and aligned to strategic outcomes.
• Drive the onboarding, configuration, and optimization of product management tools to support planning, prioritization, and roadmap delivery at scale.
• Ensure the seamless planning, execution, and enablement of Fivetran products through real-time insights and highly functional tools.

Skills We’re Looking For

• Deep technical mastery of BigQuery and SQL, with the ability to write performant, maintainable, and reusable queries from scratch.
• Experience building ground up and deploying AI/ML-powered utilities or agents using LLMs (e.g., OpenAI, Claude, etc.) to automate insights, recommendations, or user-facing tools.
• Proven experience building production-grade dashboards and data models in Looker, Sigma, or similar BI platforms.
• Strong hands-on technical acumen — you’re equally comfortable writing scripts, configuring APIs, or stitching data from multiple tools to power a cohesive end-to