The Sr. Lead AI Engineer will develop data pipelines for training AI models, ensuring data quality and processing large-scale enterprise spend data.
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 Sr. Lead AI Engineer, Data at Coupa:
Coupa's data platform already handles anonymized data exports, commodity classification, supplier normalization, and benchmark metrics across 197+ enterprise tables. The Lead AI Engineer, Data will expand this foundation, building the data curation and pipeline infrastructure that feeds our growing AI model training capabilities. This is a high-volume workstream processing trillions of dollars of enterprise spend data.
What You’ll Do
- Lead the design and implementation of data pipelines that prepare high-quality training data for AI models.
- Build data curation workflows that transform raw enterprise data into labeled, validated datasets.
- Design data quality frameworks: validation, profiling, anomaly detection, lineage tracking.
- Extend existing anonymized data export pipelines to support AI training workloads.
- Implement synthetic data generation pipelines.
- Design schema mappings across 197+ enterprise tables for feature extraction.
- Collaborate with ML engineers on training data format requirements.
- Establish data catalog and metadata management for AI training artifacts.
What You Will Bring to Coupa
- 10+ years of software engineering experience, with 5+ years in data engineering.
- Strong experience with Apache Spark / PySpark and large-scale data processing.
- Experience building ETL/ELT pipelines on cloud infrastructure (managed Spark, object storage, managed ETL, or equivalent).
- Knowledge of data quality frameworks and data governance.
- Experience with data anonymization and privacy-preserving data processing.
- Understanding of ML training data requirements.
- Proficiency in Python and SQL.
- Experience with data catalog tools and metadata management.
- BS/MS in Computer Science or equivalent experience.
- Experience in B2B SaaS with multi-tenant data preferred.
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.
Top Skills
Spark
Cloud Infrastructure
Data Catalog Tools
ETL
Managed Spark
Object Storage
Pyspark
Python
SQL
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