dbt Labs

Solutions Engineer

• Become an expert in designing enterprise-grade data pipelines with dbt Cloud
• Work hand-in-hand with sales to communicate the technical value of the dbt Labs suite of products
• Guide customers through proof-of-concept implementations and facilitate trials of dbt Cloud
• Work with engineering to deploy dbt Cloud in private clouds for enterprise clients
• Own the full customer lifecycle from pre-sale evaluation to product adoption and expansion
• Work with product to build and maintain the dbt Cloud enterprise roadmap
• Build close relationships with our Partners (including companies like Snowflake, AWS, and Databricks) and enable them to adopt and implement dbt for their clients
• Be an active member of the dbt community

Senior Solutions Architect, Enterprise

Sales

• Building out our enterprise customer base within various regions in Australia
• Identifying new business with prospects and growth opportunities for clients
• Owning the full sales cycle from lead to ongoing utilization for commercial prospects
• Organizing POC implementations of dbt Cloud Enterprise
• Leading and contributing to team projects that develop our sales process
• Working with product to build and maintain the dbt Cloud commercial roadmap
• Becoming an expert in SQL, dbt, and commercial data operations
• Being an active member of the dbt open source community

Enterprise Sales Director

Platform Engineer

• Design, operate, and scale storage based infrastructure systems across multiple tenancy models (single vs. multi-tenant) and public clouds (AWS, Azure, and GCP).
• Deepen our team’s expertise in one more areas including: relational databases, search, caching, queuing, and streaming - helping strengthen platform scalability, security, and developer experience.
• Partner with Architecture, Release Engineering, Network, Compute, and Security teams to provide a seamless platform for application teams.
• Leverage tools and languages such as Terraform, Kubernetes, Helm, Argo CD, Python, SQL, Go, Bash, and Datadog.
• Participate in a balanced on-call rotation in an environment that values continuous improvement, helping to improve reliability and reduce operational toil.

Senior Platform Engineer, Storage

Data Engineer

• Own the architecture and operations of our data lakehouse, including object storage, table formats, maintenance, and query engine integrations
• Build and maintain the infrastructure layer that transforms and serves data reliably at scale—from raw landing zones through to curated, queryable datasets
• Partner with product engineering to establish data contracts and schema standards around event telemetry, ensuring data arrives in the lakehouse in a form that's reliable and ready for downstream use
• Drive decisions on data platform architecture, tooling, and engineering best practices across storage, compute, and access layers
• Enhance observability and monitoring of data infrastructure, including pipeline reliability, data freshness, and system performance
• Partner cross-functionally with teams across Analytics, Infrastructure, and Product to understand data needs and deliver impactful platform solutions
• Provide product feedback by dogfooding new data infrastructure and AI technology

Senior Data Engineer

Engineering Manager

• Build, lead, and coach a team of 8-12 engineers to manage the infrastructure for the dbt platform and report to the Director of Infrastructure
• Empower your team to achieve big goals by giving them product and business context and supporting team ownership of the roadmap, product development lifecycle, and technical excellence.
• Dive deep into our product to frame tradeoffs and make decisions about what, how, and when we build.
• Partner with Product Marketing, Solutions Architecture, and Customer Support to build delightful migration experiences, helping our customers seamlessly move off legacy deployments.
• Coach engineers in product thinking, quality, and software engineering. Build individualized growth plans and match interests and capabilities to team goals.
• Work with peer managers to evolve organizational processes like product training, technical decision making, project execution, and planning.

Senior Engineering Manager – Infrastructure

Full-stack Engineer

• Join a senior, distributed team
• Architect and build platform infrastructure
• Drive seamless migrations
• Develop scalable backend services
• Tackle cloud networking challenges
• Automate for scale
• Collaborate and mentor
• Own and troubleshoot

Senior Platform Software Engineer, Transport

• Build, lead, and coach a team of 5–8 engineers focused on building a robust, scalable platform for AI agents.
• Architect the "Agent-First" Experience: Move dbt beyond a UI-driven tool by building the APIs and services required for agents to reason, plan, and execute within the dbt ecosystem.
• Define dbt’s MCP Strategy: Lead the development of dbt MCP tools that allow Claude, Codex, and other LLMs to fetch context, validate SQL, and understand metrics without leaving their development environment.
• Bridge Platform and Product: Partner with product teams to ensure that the AI Platform provides the necessary primitives (memory, tool-calling, and reasoning loops) for dbt’s specific agentic use cases.
• Coach engineers in building "Agent-ready" codebases—focusing on deterministic outputs from a non-deterministic world and the nuances of tool-use optimization.
• Drive Technical Excellence: Establish the standards for how agents should interact with dbt Cloud, ensuring security, governance, and auditability are never compromised for autonomy.

Manager, Software Engineering

• Own the full sales cycle from lead to ongoing utilization for commercial prospects
• Organize POC implementations of dbt Cloud Enterprise
• Lead and contribute to team projects that develop our sales process
• Work with product to build and maintain the dbt Cloud commercial roadmap
• Become an expert in SQL, dbt, and commercial data operations
• Be an active member of the dbt open source community