AI Engineer, Data Pipeline - 11318

India·BangaloreRemoteMid Levelmid

Machine Learning EngineerData

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mysqlpandaspostgresqlpythonsparksqletl

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 AI Engineer, Data Pipeline at Coupa:

Coupa's data platform processes data from hundreds of enterprise tables, powering ML models and AI features used by thousands of customers. The AI Engineer, Data Pipeline will build and maintain the data ingestion, cleansing, and transformation pipelines that support our AI platform's growing data needs.

Build data ingestion pipelines to extract and transform enterprise data.

Implement data cleansing and normalization routines.

Write and maintain ETL jobs using Spark/PySpark on cloud infrastructure.

Implement data validation and quality checks at each pipeline stage.

Build automated data export jobs for model training datasets.

Support feature extraction from enterprise schemas.

Monitor pipeline health, troubleshoot failures, and optimize performance.

Document data lineage, schemas, and transformation logic.

3+ years of software engineering experience.

Experience with Python and data processing (pandas, PySpark, or equivalent).

Familiarity with SQL and relational databases (MySQL, PostgreSQL).

Experience with cloud data services (object storage, managed Spark, managed ETL, or equivalent).