Lead Analytics Engineer

Coupa makes margins multiply through its community-generated AI and industry‑leading total spend management platform for businesses large and small. Coupa AI is informed by trillions of dollars of direct and indirect spend data across a global network of 10M+ buyers and suppliers. We empower you with the ability to predict, prescribe, and automate smarter, more profitable business decisions to improve operating margins. Why join Coupa? Pioneering Technology: At Coupa, we’re at the forefront of innovation, leveraging the latest technology to empower our customers with greater efficiency and visibility in their spend. Collaborative Culture: We value collaboration and teamwork, and our culture is driven by transparency, openness, and a shared commitment to excellence. Global Impact: Join a company where your work has a global, measurable impact on our clients, the business, and each other. Learn more on Life at Coupa blog and hear from our employees about their experiences working at Coupa. The Impact of a Lead Analytics Engineer at Coupa 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 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 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 Coupa complies with relevant laws and regulations regarding equal opportunity and offers a welcoming and inclusive work environment. Decisions related to hiring, compensation, training, or evaluating performance are made fairly, and we provide equal employment opportunities to all qualified candidates and employees. Please be advised that inquiries or resumes from recruiters will not be accepted. By submitting your application, you acknowledge that you have read Coupa’s Privacy Policy and understand that Coupa receives/collects your application, including your personal data, for the purposes of managing Coupa’s ongoing recruitment and placement activities, including for employment purposes in the event of a successful application and for notification of future job opportunities if you did not succeed the first time. You will find more details about how your application is processed, the purposes of processing, and how long we retain your application in our Privacy Policy. #J-18808-Ljbffr