Staff Software Engineer - Semantic Layer

About the role

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 dbt Labs Since 2016, dbt Labs has been on a mission to help analysts create and disseminate organizational knowledge. dbt has become an open-source standard, used by over 50,000 companies worldwide to transform data in their warehouses. Our work shapes how modern data teams operate, and we're now extending that impact from transformation into the semantic layer - the foundation for trusted, governed metrics across every analytics and AI workflow. We're building a remote-first, globally distributed team, and we're growing our engineering presence in India to bring senior talent closer to the products defining the future of data. The Semantic Layer team owns the systems that turn dbt models into trusted, reusable business metrics. At the heart of this is MetricFlow - the open-source semantic engine that powers the dbt Semantic Layer. MetricFlow lets data teams define metrics once in code and consume them consistently across BI tools, notebooks, AI agents, and downstream applications. This team is the steward of MetricFlow as an open-source project: shipping releases, reviewing community contributions, evolving the query compiler, and ensuring it integrates cleanly with the broader dbt ecosystem. You'll work at the intersection of language design, query compilation, and distributed data execution - solving problems that directly shape how thousands of organizations measure their business. We're hiring a Senior Software Engineer to join the Semantic Layer team in Bangalore. You'll be a core contributor to MetricFlow - designing features, optimizing query generation, hardening the open-source codebase, and partnering with the community of contributors and adopters around it. This is a high-ownership role: you'll write production code, drive technical decisions, and help shape the long-term architecture of one of the most important projects in the modern data stack.

Responsibilities

• Design, build, and maintain core features of MetricFlow, including metric definitions, query compilation, dimensional modeling, and SQL generation across multiple data warehouses (Snowflake, BigQuery, Databricks, Redshift, and others).
• Own MetricFlow as an open-source project - triage issues, review external pull requests, manage releases, and engage the community on GitHub and in Slack.
• Collaborate with engineers across dbt Cloud, dbt Core, and the Semantic Layer service to ensure MetricFlow integrates seamlessly with the rest of the dbt ecosystem.
• Improve performance, reliability, and observability of metric query execution at scale.
• Partner with product, design, and developer-relations teammates to translate customer and community feedback into shipped improvements.
• Write clear technical documentation, RFCs, and design docs that raise the bar for how the team thinks and ships.
• Mentor other engineers through code review, pairing, and technical guidance.

Requirements

• Strong professional software engineering experience, with a strong track record of shipping production systems.
• Deep proficiency in Python , including modern typing, testing practices, and packaging.
• Strong SQL fundamentals and a working understanding of how analytical query engines and data warehouses execute queries.
• Experience designing systems that involve parsing, compilation, or transformation - for example: query planners, DSL compilers, type systems, or rule-based engines.
• Solid grasp of software design principles: clean APIs, modularity, testability, and backwards compatibility.
• Excellent written and verbal communication - you can explain complex tradeoffs clearly to engineers, PMs, and external community members.
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