Senior Analytics Engineer

Ironclad is the leading AI contracting platform that transforms agreements into assets. Contracts move faster, insights surface instantly, and agents push work forward, all with you in control. Whether you’re buying or selling, Ironclad unifies the entire process on one intelligent platform, providing leaders with the visibility they need to stay one step ahead. That’s why the world’s most transformative organizations, from Rivian to the World Health Organization and the Associated Press, trust Ironclad to accelerate their business. We’re consistently recognized as a leader in the industry: a Leader in the Forrester Wave and Gartner Magic Quadrant for Contract Lifecycle Management, a Fortune Great Place to Work, and one of Fast Company’s Most Innovative Workplaces. Ironclad has also been named to Forbes’ AI 50 and Business Insider’s list of Companies to Bet Your Career On. We’re backed by leading investors including Accel, Y Combinator, Sequoia, BOND, and Franklin Templeton. For more information, visit www.ironcladapp.com http://www.ironcladapp.com or follow us on LinkedIn. ABOUT THE ROLE 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

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