Senior Software Engineer II

About Us dbt Labs is the pioneer of analytics engineering, helping data teams transform raw data into reliable, actionable insights. Since 2016, we’ve grown from an open source project into the leading analytics engineering platform, now used by over 90,000 teams every week, driving data transformations and AI use cases. As of February 2025, we’ve surpassed $100 million in annual recurring revenue (ARR) and serve more than 5,400 dbt Platform customers, including AstraZeneca, Sky, Nasdaq, Volvo, JetBlue, and SafetyCulture. We’re backed by top-tier investors including Andreessen Horowitz, Sequoia Capital, and Altimeter. At our core, we believe in empowering data practitioners: Reliable, high-quality data is the fuel that propels AI-powered data engineering. AI is changing data work, fast. dbt’s data control plane keeps data engineers ahead of that curve. We empower engineers to deliver reliable, governed data faster, cheaper, and at scale. dbt Labs is now synonymous with analytics engineering, defining the modern data stack and serving as the data control plane for enterprise teams around the world. And we’re just getting started.. We’re growing fast and building a team of passionate, curious people across the globe. Learn more about what makes us special by checking out our values . About the Role Analytics is entering an agentic era. As a Senior Software Engineer on Agentic Automation ADLC Systems, you will build the autonomous and assisted agents that operate across the Analytics Development Life Cycle (ADLC) — from requirements to deployment to remediation. These agents don’t just automate tasks. They reason over enterprise context , act on data products , and leave behind decision memory that improves the system over time. What You’ll Do Build agentic systems that automate analytics workflows across the ADLC Design and implement agents for: Requirements intent capture Build validation Test deploy Operate, observe, and remediate Orchestrate agent workflows using event-driven triggers Integrate agents with ingestion and transformation workflows Encode governance and decision policies into automation Ensure every agent action is explainable, attributable, observable and auditable Balance autonomy with human-in-the-loop controls What You’ll Own Agent behavior and orchestration logic ADLC automation workflows, governance expressed as executable logic Agent interaction with the Context Platform Safe auto-remediation and escalation paths, observability and feedback/recovery loops What You Won’t Own Context storage or schema design Low-level platform security primitives Long-term data durability decisions (You consume these via the Context Platform.) What We’re Looking For Strong experience in backend, platform, or systems engineering Experience building automation, workflows, or orchestration systems, familiarity with event-driven architectures Understanding of data/documentation tools, integration nuances, their information systems. Hands-on experience building systems with LLMs or agentic systems (practical, production-minded) Strong intuition for safety, failure modes, and guardrails, AI observability Exposure to working with structured, semi-structured and unstructured data. Nice to Have Experience with CI/CD or developer tooling Familiarity with analytics engineering or dbt Experience integrating with human workflow tools (GitHub, Slack, Jira, Notion) Background in reliability/resilience engineering Why This Role Matters If these agents are built correctly: Analytics workflows accelerate without losing trust Governance becomes proactive, not reactive Humans focus on decisions, not plumbing This role turns context into action. dbt Labs is an equal opportunity employer, committed to building an inclusive team that welcomes diverse perspectives, backgrounds, and experiences. Even if your experience doesn’t perfectly align with the job description, we encourage you to app ... (truncated, view full listing at source)