Senior Lead Software Engineer, Coupa

• 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

Desirable

• This is a senior, hands-on individual contributor role with high ownership and technical depth
• A key part of the role is continuously improving latency, reliability, and performance as the platform scales
• You will work on challenging, real-world data problems—ranging from high-throughput ingestion to enabling sub-second data retrieval and query performance—while influencing architecture and best practices across the broader data ecosystem
• If you enjoy solving complex data platform problems, working close to production systems, and seeing your work directly impact customers, this role offers constant opportunities to make a meaningful impact without becoming repetitive
• 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