As a Lead Analytics Engineer at Coupa, you'll architect the data foundation that powers strategic decisions across the organization. You'll transform raw data into trusted, reusable data products using DBT and modern data tools—building the semantic layers that enable self-service analytics while maintaining data quality and governance. This is where data engineering craft meets business impact.
What You'll Do:
Build Data Products
Design and build dimensional models, data marts, and semantic layers using DBT that serve as the single source of truth
Create modular, reusable data transformations that embody business logic and can be leveraged across multiple use cases
Develop comprehensive documentation that makes your models accessible to all users
Partner with the Business
Collaborate with stakeholders to deeply understand business domains, metrics, and analytical needs
Translate complex requirements into scalable data architectures and logical models
Design data structures that support both reporting and operational analytics
Drive Technical Excellence
Write clean, efficient, performant SQL for large-scale data processing in Snowflake
Implement data quality checks, testing frameworks, and monitoring to ensure reliability
Leverage Git, CI/CD, and software engineering best practices in analytics workflows
Lead & Mentor
Establish and evangelize best practices in analytics engineering and DBT development
Mentor junior engineers through code reviews and technical guidance
Contribute to the evolution of our data architecture and development standards
Collaborate with US-based teams to gather and understand business requirements.
What You Will Bring to Coupa:
6+ years of hands-on experience with the modern data stack (DBT, Snowflake, SQL) and expert-level SQL skills, including query optimization.
Strong proficiency in DBT — macros, packages, incremental models, testing, and documentation.
Deep understanding of dimensional modeling, star schemas, and data warehouse design patterns.
Experience using Python and/or Ruby for data transformation and automation.
Proven ability to collaborate with business stakeholders, translate requirements into technical solutions, and deliver reusable data products for self-service analytics.
Strong communicator with experience leading projects and mentoring team members across technical and non-technical domains.
