Senior Lead AI Engineer, Data

🕒 March 31

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 45%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Coupa Software

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2006

💼 Consulting

📦 Logistics

🏥 Healthcare

Consulting • Logistics • Healthcare

Coupa Software is a leading provider of business spend management solutions. Their platform focuses on optimizing and transforming direct and indirect spend across procurement, finance, supply chain, and IT. Coupa leverages AI and extensive data insights to drive cost efficiencies, manage supplier relationships, and mitigate risks. With products covering areas such as invoicing, payments, expense management, and supply chain collaboration, Coupa serves a wide range of industries including automotive, healthcare, retail, and more. Their comprehensive community and partner ecosystem enable organizations to unlock hidden savings and improve compliance, promoting growth and resilience in a changing economic climate.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Pioneering Technology • Collaborative Culture • Global Impact