Senior Data Engineer

About USP

The U.S. Pharmacopeial Convention (USP) is an independent scientific organization that collaborates with the world’s leading health and science experts to develop rigorous quality standards for medicines, dietary supplements, and food ingredients. USP believes that scientific excellence is driven by a commitment to fairness, integrity, and global collaboration. This belief is embedded in our core value of Passion for Quality and is demonstrated through the contributions of more than 1,300 professionals across twenty global locations, working to strengthen the supply of safe, high‑quality medicines worldwide.

We are seeking a high‑energy, hands‑on Data Engineer to design, build, and maintain scalable, production‑grade data pipelines across our AWS‑based data platform. This role will own end‑to‑end pipeline delivery—from enterprise system ingestion to creating analytics‑ready datasets—while working closely with Data Architects, Analytics teams, and business stakeholders. You will help evolve our AWS Lakehouse architecture and shape best practices.

As part of our mission to advance scientific rigor and public health standards, you will play a vital role in increasing global access to high‑quality medicines through public standards and related programs. USP prioritizes scientific integrity, regulatory excellence, and evidence‑based decision‑making to ensure health systems worldwide can rely on strong, tested, and globally relevant quality standards. Our People and Culture division, in partnership with the Equity Office, invests in training to equip employees with skills that create high‑performing, inclusive teams.

• Data Pipeline Development: Design, develop, and maintain scalable ELT pipelines with reusable ingestion frameworks supporting batch and event‑driven workflows across diverse sources including ERPs, APIs, vendor files, and relational databases.
• AWS Cloud Data Engineering: Build and optimize AWS‑native data pipelines implementing a Medallion Lakehouse architecture with a focus on performance and cost efficiency.
• Infrastructure, CI/CD & Dev Ops: Provision and manage AWS infrastructure via Terraform, maintaining CI/CD pipelines with Git Ops practices, automated testing, logging, alerting, and recovery mechanisms for production systems.
• Data Modeling & Transformation: Design and implement dimensional models, Gold‑layer datasets, and scalable vendor file ingestion patterns using SQL, Python, and PySpark, with robust handling of schema drift, audit tracking, and query optimization through partitioning, clustering, and materialization strategies.
• Data Quality & Governance: Implement automated data validation, anomaly detection, and lineage tracking within pipelines while supporting metadata management.
• Reporting & Power BI Support: Troubleshoot and resolve complex data issues while ensuring pipelines deliver data in formats optimized for Power BI; collaborate with Power BI developers to align data structures with reporting requirements and resolve dashboard‑related data issues.
• Collaboration & Continuous Improvement: Partner with Architects and Analytics teams to translate business needs into technical solutions, actively contributing to code reviews, architecture discussions, sprint planning, and more.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent combination of education and experience.
• Minimum 7+ years of data engineering experience, with strong expertise in AWS services and hands‑on work with big data and distributed data technologies in the AWS cloud environment.
• Strong proficiency in Python and SQL with experience in PySpark/Spark.
• Hands‑on experience building and operating data pipelines on AWS (Glue, Step Functions, Lambda, S3, Athena, SNS, SQS, Redshift, etc.).
• Demonstrated experience with event‑driven pipeline architectures.
• Experience ingesting and processing vendor‑supplied data files on a large scale.
• Practical experience implementing Medallion (Bronze/Silver/Gold) architecture in a data lake or Lakehouse environment.
• Experience with Terraform for cloud infrastructure…