Coupa Software-posted 3 months ago
$144,075 - $212,000/Yr
Full-time • Senior
Hybrid • Foster City, CA
1,001-5,000 employees
Publishing Industries

As a Lead Software Engineer, you'll play a key role in building and scaling Coupa's data infrastructure to support real-time decision-making across global operations. You'll design and optimize high-performance data pipelines and Spark clusters on AWS, ensuring seamless data integration, automation, and availability. Your work will directly enhance Coupa's analytics capabilities, empower internal teams with trusted insights, and drive smarter, faster business decisions through secure, scalable, and AI-enabled data solutions.

  • Design, build, and maintain highly scalable and efficient data pipeline architectures, ensuring seamless data integration and high availability.
  • Lead the optimization of Spark clusters, implement advanced monitoring, and proactively identify and resolve performance bottlenecks for continuous improvement.
  • Orchestrate the assembly and delivery of large, complex datasets that align with critical business requirements, while automating data processes and significantly enhancing data delivery efficiency.
  • Architect robust data extraction, transformation, and loading (ETL) infrastructure using SQL and advanced AWS big data technologies, developing sophisticated analytics tools to drive actionable business insights.
  • Spearhead collaboration with cross-functional teams to resolve complex data-related issues, ensure stringent data security across AWS regions, and empower data scientists to optimize advanced product functionalities.
  • 8-12 years of data engineering experience with deep expertise in big data (Spark, Kafka), cloud platforms (AWS), and orchestration tools (Airflow, Luigi).
  • Advanced degree in a quantitative field; expert in SQL, relational databases, query optimization, and diverse database systems.
  • Extensive experience in building and optimizing Spark clusters, scalable data pipelines, and ingestion systems across structured/unstructured data.
  • Proven skills in designing cloud-native, API-centric data architectures using REST/GraphQL, with strong support for analytics and reporting.
  • Strong background in data governance, quality control, microservice orchestration, and performance monitoring.
  • Proficient in applying AI/ML techniques for data classification, harmonization, and predictive analytics.
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