Principal Software Engineer, AI Tooling & Adoption

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.  Fivetran is seeking an exceptional Principal Software Engineer to lead our AI adoption initiative across the Engineering organization. This unique leadership role combines deep technical expertise with strategic business acumen and change management capabilities. You will be the driving force behind transforming our 500+ engineers into “Bionic Engineers" while implementing Virtual Engineer capabilities to achieve 10% productivity gains in FY26 and 20% in FY27. As the single point of contact for AI initiatives in Engineering, you will orchestrate an engineering-wide transformation that makes AI-driven productivity a core engineering competency. This role requires someone who can navigate the rapidly evolving AI landscape, drive adoption across diverse teams, and deliver measurable business impact. This is a full-time position based out of our Oakland 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 Java, Postgres, Oracle, SQL Server, MySQL, Kubernetes, Docker, AWS, GCP, CircleCI Google Gemini, Anthropic Claude, Claude Code, ChatGPT, OpenAI Codex, GitHub Copilot What You’ll Do Adoption Management & Leadership (40%) Drive Cultural Transformation: Lead the evolution from AI-curious to AI-native engineering practices across all teams Champion Change Management: Convert skeptics into advocates through data-driven demonstrations of value and hands-on enablement Measure & Accelerate Adoption: Establish KPIs, track progress from the current 50% to 100% adoption, and implement interventions to accelerate uptake Build Communities of Practice: Create forums for knowledge sharing, celebrate wins, and foster peer-to-peer learning Technical Leadership (35%) Tool Evaluation & Selection: Continuously assess emerging AI tools (Copilot, Claude Code, Codex, etc.) and make data-driven recommendations Architecture & Integration: Design technical frameworks for integrating AI tools into existing development workflows and CI/CD pipelines Virtual Engineer Implementation: Lead proof-of-concepts for coding agents in standardized tasks (Lite Connectors via CoIL, code refactoring, test generation) Security & Compliance: Partner with Security and Legal teams to ensure AI tool usage protects IP and meets compliance requirements Technical Standards: Establish best practices, guidelines, and guardrails for AI-assisted development Performance Optimization: Analyze and optimize the technical performance and cost-efficiency of AI tool deployments Innovation Pipeline: Maintain awareness of cutting-edge AI developments and identify opportunities for competitive advantage Business Leadership (25%) Strategic Planning: Develop and execute the three-phase AI adoption roadmap (Explore & Learn → Enable, Train & Adopt → Core Competency) Budget Management: Oversee $1M+ annual tool budget, optimize spend across 500+ team members, and demonstrate ROI Stakeholder Management: Build relationships with the CEO, Engineering Leadership, Finance, L&D,