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Senior Analytics Engineer

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Salary

$147,000 - $184,000

Location

San Francisco, CA

Posted

2 days ago

As a Senior Analytics Engineer, you will be responsible for developing and optimizing our dbt infrastructure, implementing scalable data models, and ensuring consistent business logic across a fast-growing organization. You will partner cross-functionally with analytics, data science, data engineering, and data-savvy business stakeholders to design reliable and consistent datasets that serve as the foundation for understanding our business.

In this role, you will play a pivotal part in our AI transformation. You will leverage AI to boost the efficiency of our own data pipelines while architecting "AI-ready" data assets that empower our analytics and business teams to perform advanced, LLM-driven analysis.

This role will report into the Sr. Manager of Analytics Engineering.

What you'll do

  • Data Transformation: Design and maintain transformations that ensure accurate, scalable, and high-quality datasets as the bedrock of our data warehouse.
  • dbt Architecture: Serve as the Architect for our dbt project, evolving the architecture, design patterns, and best practices to ensure consistent data definitions and streamlined development.
  • Metric Unification: Standardize metrics across our BI tools to drive seamless self-service analytics in Looker and high-accuracy results in AI-powered exploration tools.
  • Team Mentorship: Provide guidance and code reviews to analysts and analytics engineers, fostering a culture of collaboration and excellence in dbt and data modeling.
  • Workflow Modernization: Integrate AI-assisted workflows (e.g., Claude Code) into the development lifecycle to accelerate code generation, documentation, and testing.
  • AI Context Engineering: Architect "AI-ready" data by designing enriched metadata and context guides that enable intuitive, natural-language data exploration for business users.
  • Stack Collaboration: Partner with Data Engineering to design ingestion and transformation pipelines that are scalable, efficient, and aligned with business needs.
  • Data Governance: Champion data privacy and quality by upholding governance processes and compliance measures to maintain the highest standards of integrity.

What we're looking for

  • Experience: 5+ years as an analytics engineer, data engineer, or business intelligence engineer, with 2+ years developing in dbt (ideally within B2B SaaS).
  • SQL Mastery: Advanced proficiency in SQL and a strong grasp of data modeling.
  • AI-Assisted Development: Proficiency in leveraging AI coding assistants (e.g., Cursor, Claude Code) to accelerate dbt development, documentation, and the creation of robust data tests.
  • Context Engineering: Experience (or a strong interest) in building "AI-ready" documentation. You understand how to write effective Markdown guides, table descriptions, and metadata that help humans and LLMs navigate our data with high confidence and minimal hallucination.
  • Modern Stack Knowledge: Hands-on experience with our core tools (Fivetran, BigQuery, dbt, Github, Airflow, Looker) or their equivalents and modern exploration platforms like Hex.
  • Critical Thinking: A naturally inquisitive problem-solver who enjoys deconstructing complex business challenges and finds the most pragmatic path to a solution.
  • Ownership & Communication: A demonstrated self-starter with the project management skills to lead initiatives and the communication clarity to bridge the gap between technical teams and business stakeholders.

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