Sr. Lead Software Engineer - 11282

Coupa is a company that specializes in total spend management through its innovative AI-driven platform. The Sr. Lead Software Engineer will design and implement scalable data ingestion systems, build core data platform components, and provide technical leadership while working on complex data problems across a multi-cloud environment.

Responsibilities:

• Design and implement scalable, high-throughput data ingestion systems that integrate internal and external data across domains
• Design and build core data platform components, including ingestion, validation, orchestration, and lineage, with a focus on code quality and reliability
• Build and evolve a centralized data lake using Apache Iceberg (or similar table formats)
• Work across multi-cloud environments (AWS, GCP, Azure) to design and implement cloud-agnostic data ingestion and processing patterns
• Contribute hands-on to the Semantic layer, ensuring data is easy to consume for BI and analytics teams
• Partner with Senior Data Engineers, Platform Engineers, and Analytics Engineers to align how data is produced, stored, and consumed
• Establish practical engineering standards for testing, observability, and operational excellence
• Provide technical leadership through mentorship, code reviews, and design discussions, while remaining hands-on

Requirements:

• 8-10+ years of experience in software or platform engineering, with a focus on building scalable data and analytics platforms
• Strong understanding of data ingestion patterns at scale, including CDC, and how data should be modeled and stored in a data lake for fast, efficient retrieval
• Proven experience building and operating large-scale data pipelines in production
• Experience working with modern data warehouses such as Databricks, BigQuery, or Snowflake
• Strong proficiency in Python and SQL, with a focus on writing production-quality, maintainable, and testable code
• Hands-on experience working with cloud data services in AWS, GCP, or Azure
• Experience working with query engines such as Presto or Trino to enable fast, reliable analytics over data lakes
• Familiarity with Lakehouse architectures and table formats such as Iceberg or Delta Lake
• Familiarity with data governance, lineage, metadata, cataloging, and data quality practices
• Nice to have exposure to semantic layers, metrics frameworks, or BI-friendly data modeling
• Experience supporting analytics or AI/ML workloads