> Markdown version of [/jobs/ext/1893472-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/1893472-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer - **Company:** Ironclad, Inc. - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $147,000.0 - $184,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Data Analysis, Business Logic, BigQuery, Software as a Service, Software Documentation, Code Generation, Code Review, Information Engineering, Data Files, Data Governance, Data Transformation, Data Warehousing, Cursor (Graphical User Interface Elements), Software Design Patterns, Github, Apache Maven, Metadata, Markdown, Software Engineering, SQL Databases, Large Language Models, Data Management, Looker Analytics, Data Pipelines - **Published:** July 31, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-analytics-engineer-san-francisco-ca--40dad316-9141-4556-b740-1fa53defad68 ## About the Role * 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., Analysis Skills, Architectural Design, Artificial Intelligence (AI), Associated Press, Best Practices, Business Intelligence, Business Intelligence Software, Business-to-Business (B2B), Coaching, Code Reviews, Contract Management, Cross-Functional, Data Management, Data Modeling, Data Science, Data Sets, Data Warehousing, Design Patterns Programming Methodologies, Documentation, GitHub, Insider List, Leadership, LinkedIn, Looker, Maven, Mentoring, Metadata, Metrics, People Management, Problem Solving Skills, Product Lifecycle, Psychiatry and Mental Health, Sales, Software as a Service (SaaS), Testing, User Documentation, World Health Organization (WHO) ## Description 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) ## Related Articles - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Dev Digest 139 - Soft and hard queries](https://www.wearedevelopers.com/magazine/487-dev-digest-139-soft-and-hard-queries) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)