Senior Analytics Engineer

Design and build our data models and transformations, applying software engineering best practices in dbt on top of our Google BigQuery warehouse to produce datasets that are accurate, performant, and easy to reason about. Own the semantic layer in Lightdash, defining metrics, dimensions, and governed datasets so the business gets one consistent, trusted answer to every question - no matter who (or what) is asking. Act as a leader for our data modeling standards, shaping conventions, review practices, and documentation that keep the transformation layer maintainable as it grows. Develop end-to-end with AI coding agents. Our teams build with Claude Code and similar tools, and you'll use AI-assisted workflows to move faster while upholding quality through testing and review. Enable AI-driven analytics, treating the semantic and governance layers as the foundation that agents and MCP connections build on to deliver trustworthy, self-serve answers from data. Advance metric governance and definitional consistency, contributing to the auditability and reporting rigor expected of a company operating at scale and under growing scrutiny. Partner with cross-functional stakeholders to gather requirements, identify high-value reporting and dashboarding use cases, and ship the models and metrics that drive decisions. Train and enable users on self-serve analytics capabilities and best practices, growing the number of people across the business who can confidently answer their own questions with data. Requirements An experienced analytics engineer with 5+ years in analytics engineering, data engineering, or a similar role, with a proven ability to model data for reporting and analytics needs. Highly experienced with dbt, applying the best practices of software engineering - modularity, testing, code review, documentation - to data transformation. An expert in the modern data stack, with hands-on experience across cloud data warehousing (BigQuery or equivalent), data transformation, and workflow orchestration. Experienced with a modern BI / semantic layer such as Lightdash, Looker, or similar - and opinionated on where the metrics layer is heading and why it matters more, not less, in an agentic world. Fluent in AI-assisted development. You have real experience developing with Claude Code or a similar coding agent, or you're eager to make AI-driven workflows a core part of how you build. Analytically minded. You have experience with or a strong interest in the analytical side of data - collecting requirements, defining and implementing metrics, and developing dashboards that tell a clear story. A strong cross-functional partner. You build trust with stakeholders easily, translate business questions into well-modeled data, and communicate clearly with both technical and non-technical audiences. Technically fluent. You're proficient in SQL and Python, with a strong working knowledge of software engineering workflow tools such as version control, CI/CD, and testing. Core Competencies Demonstrates expertise in data modeling and transformation using dbt and Google BigQuery, with a strong focus on metric governance and self-serve analytics. Proficient in SQL and Python, with experience in AI-assisted development and cross-functional collaboration. Highest-signal resume keywords Analytics Engineering Data Transformation with dbt Google BigQuery Lightdash or Similar BI Tools AI-Assisted Development ATS Optimization Keywords Hard Skills SQL Python Data Modeling Data Governance Metric Definition Dashboard Development Testing Code Review Documentation Workflow Orchestration Soft Skills Cross-Functional Collaboration Stakeholder Communication Analytical Mindset Trust Building Industry Keywords Modern Data Stack Semantic Layer Self-Serve Analytics Data Warehousing Reporting Rigor Tools & Technologies Dbt Google BigQuery Lightdash Claude Code CI/CD Tools #J-18808-Ljbffr