[Remote] Data Engineer
Note: The job is a remote job and is open to candidates in USA. K3-Innovations, Inc. is seeking a Data Intelligence Engineer to support a Computational Drug Discovery team. The role focuses on building scalable databases, data ingestion and integration pipelines, and workflows that improve access to scientific and machine-learning data, model results, and insights.
Responsibilities
- Design and create relational database tables and schemas to support model inventories, metadata, model metrics, and model results
- Build and maintain data ingestion and integration workflows for scientific and machine-learning results
- Develop staging tables and processes to manage new data, inserts, updates, and integrations
- Integrate results from multiple sources, including:
- Machine learning models
- Co-folding/affinity prediction workflows
- MPO calculations
- FEP+ and physics-based scoring
- Other computational chemistry and scientific calculations
- Develop Python scripts and automation to improve data ingestion and processing
- Support containerization and deployment of computational models using Docker and cloud environments such as AWS EC2
- Collaborate with computational scientists to define appropriate data structures, metadata, and workflows
- Support API-based model deployment and integration where applicable
- Evaluate open-source tools and technologies for scientific data and computational workflows
- Develop virtual molecule enumeration workflows using Free-Wilson or matched molecular pair (MMP) transformations, when applicable
- Ensure data workflows are reliable, reproducible, scalable, and well documented
Skills
- 5–7 years of relevant experience in data engineering, scientific data management, computational chemistry, cheminformatics, or a related field
- Strong hands-on experience with Python and SQL
- Experience designing and maintaining relational databases and database schemas
- Experience building data ingestion, ETL, staging, and integration pipelines
- Experience working with scientific or machine-learning datasets
- Familiarity with Docker/containerization
- Experience with AWS EC2 or similar cloud environments
- Understanding of machine-learning models, model metadata, and model-result tracking
- Strong scripting, automation, problem-solving, and communication skills
- Experience in Computational Drug Discovery (CDD) or pharmaceutical R&D
- Knowledge of cheminformatics and molecular data
- Familiarity with Free-Wilson analysis, MMPs, or virtual molecule enumeration
- Experience with FEP+ or related computational chemistry methods
- Experience with scientific ontologies and data standardization
- Experience deploying scientific models through APIs or self-service platforms
Benefits
- Remote work
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