Senior Analytics Engineer

About the role

The Senior Analytics Engineer plays a pivotal part in Ironclad's AI transformation. They design and maintain transformations that ensure accurate, scalable, and high-quality datasets serving as the foundation for understanding the business. They also partner cross-functionally with analytics, data science, data engineering, and business stakeholders to design reliable and consistent datasets.

Responsibilities

• 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.

Requirements

• 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.

Qualifications

• Experience with dbt and its ecosystem.
• Strong understanding of data modeling and SQL.
• Experience with modern data stack tools and platforms.
• Ability to work collaboratively with cross-functional teams.
• Experience with AI and machine learning concepts.

Skills

• Advanced SQL and data modeling skills.
• Experience with dbt and related tools.
• Proficiency in modern data stack technologies.
• Experience with AI and machine learning concepts.
• Excellent communication and mentoring skills.

Benefits

• Base Salary Range: $147,000 - $184,000
• Comprehensive health and wellness benefits.
• Flexible leave policies.
• Annual stipends for wellbeing, hybrid work, and cell phone use.
• Pre-tax commuter benefits.
• 401(k) plan with employer match.
• Regular team events.