Note: The job is a remote job and is open to candidates in USA. Insight Global is a leading global pharmaceutical organization seeking a Senior Data Engineer to help build the data foundation for a next-generation AI-enabled drug discovery platform. The role involves designing and delivering a cloud-native scientific data product that supports molecular design and computational chemistry workflows.
Responsibilities
- Design, build, and own a new enterprise scientific data product supporting computational chemistry and molecular design initiatives
- Develop scalable cloud-native data architecture capable of managing large scientific and chemistry-derived datasets
- Create and optimize data models, schemas, and storage structures that support future AI/ML and analytics use cases
- Build and maintain data ingestion, transformation, and orchestration pipelines using Python
- Develop data solutions utilizing Google Cloud Platform (GCP) and BigQuery
- Integrate data from scientific systems, computational chemistry platforms, laboratory environments, and external data sources
- Design solutions that preserve scientific lineage, design history, traceability, and molecular decision-making workflows
- Partner with computational chemists and scientists to model molecular design, reaction, synthesis, and experimental data
- Ensure datasets are analytics-ready, trusted, scalable, and easily consumable by researchers, applications, and machine learning platforms
- Build and maintain CI/CD processes, testing frameworks, and deployment automation
- Implement data quality, observability, metadata management, and governance standards
- Support future AI, machine learning, and agent-driven drug discovery initiatives through scalable data architecture design
- Provide technical leadership on database design, schema evolution, performance optimization, and long-term platform scalability
Skills
- Bachelor's or Master's degree in Chemistry, Life Sciences, Bioinformatics, Computer Science, Data Engineering, or a related discipline
- Experience working with scientific datasets, chemistry data, computational chemistry data, or research data platforms
- Experience developing enterprise-scale ETL/ELT pipelines
- Experience managing large, complex datasets in scientific, pharmaceutical, or R&D environments
- Experience with one or more cheminformatics tools: ChemAxon, RDKit, BIOVIA, Pipeline Pilot
- Experience implementing CI/CD pipelines and modern software development practices
- Strong understanding of cloud-native architecture and data platform scalability
- Strong experience in: Data Engineering, Data Product Development, Database Architecture, Schema Design, Data Modeling
- Hands-on experience with: Google Cloud Platform (GCP), BigQuery, Python, SQL
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