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Salary: USD 115,000 - 175,000 / annual
Veeva Systems, a public benefit corporation and pioneer in industry cloud for life sciences, is seeking a Senior Data Engineer to join the NitroAI team. This is a high-ownership role within a startup-like environment, responsible for building and maintaining the data engineering infrastructure that powers analytics delivery across a growing multi-tenant platform.
You will own the Airflow codebase end-to-end, managing approximately 100 DAGs on AWS MWAA. Key responsibilities include building reusable templates, scaling patterns, enforcing standards, and improving testing infrastructure. You'll serve as the go-to resource for delivery teams on pipeline architecture and troubleshooting, and own the complete data onboarding process when connecting to new sources—from connection setup through schema discovery to initial pipeline design.
You will operate and extend large-scale Spark pipelines on AWS Glue, handling multi-TB joins and compaction jobs, while supporting the migration of these workloads to Databricks. You'll drive data model improvements around commercial pharma data (patient claims, KOL and HCP data, CRM activity), focusing on structure, lineage, and platform flow. Additionally, you'll contribute to and maintain the internal Python package used across the data team.
Required qualifications include 5+ years building data models and pipelines, 2+ years of production Airflow experience, and 2+ years working with Spark at scale on multi-TB datasets (AWS Glue experience preferred). You must have strong Python and SQL skills, AWS fluency (S3, ECS/Fargate, Glue, IAM, Secrets Manager), and excellent communication abilities, particularly in teaching and onboarding analytics teams to the codebase.
Nice-to-have skills include experience with privacy-sensitive or governed data, Databricks, Claude Code, data science workflows, ML pipeline tooling, life sciences or healthcare background, and familiarity with data catalog tools like Open Metadata.
