Senior Data Engineer

Job Title: Senior Data Engineer – Scientific & R&D Data Platforms Location: Upper Providence, PA Type: 12 Month Contract Hours: Standard business hours Compensation: $72 – $91/hour Overview A leading science‑driven organization is seeking a Senior Data Engineer to design and deliver a new enterprise data product supporting generative drug design and computational chemistry platforms. This role is focused on building scalable, well‑structured data architecture from the ground up, with long‑term expansion and downstream AI/ML integration in mind. The ideal candidate brings strong data engineering fundamentals, hands‑on cloud experience, and an understanding of scientific or chemistry‑driven data workflows within life sciences or R&D environments. Key Responsibilities • Design and implement a new enterprise data product, initially delivered as a standalone solution with future integration into AI‑driven drug discovery platforms • Build scalable data pipelines, schemas, and storage models to support large, complex scientific and chemistry‑derived datasets • Develop and maintain data solutions primarily on GCP and BigQuery, aligned with enterprise engineering standards • Implement data transformations and pipelines using Python, with an emphasis on data quality, traceability, and performance • Ensure the data architecture supports future expansion, additional datasets, and evolving analytical and computational needs • Partner closely with computational chemists, data scientists, and ML engineers to align data models with generative design workflows and ML outputs • Apply drug design and chemistry concepts (molecular properties, structure‑activity data, experimental results) to inform data modeling decisions • Provide technical guidance around scalability, data structure, and long‑term maintainability in an enterprise environment Required Skills • Strong experience in data engineering, including database design, schema modeling, and data product architecture • Hands‑on experience with GCP and BigQuery (Postgres familiarity is a plus) • Proficiency in Python for building and maintaining data pipelines • Onyx platform or ecosystem experience • Experience working with large, complex datasets at scale, ideally in scientific or R&D settings • Background in life sciences, pharma, or scientific data platforms Plusses • Experience supporting downstream analytics, ML pipelines, or AI‑driven platforms • Exposure to generative design, discovery platforms, or computational research environments • Working knowledge of drug design, chemistry, or computational chemistry data