Principal Data Scientist – Therapeutics Data & AI Pipelines

Jobtailor; Spring House (PA); On-site; USD 110,000 - 170,000; Full time

Job summary

Jobtailor is seeking a data engineer to design and maintain scalable data pipelines for Therapeutics Development & Supply data. You will optimize data flows with Python, R, SQL, DBT, and cloud services, and develop enterprise-level data models aligned for AI/ML readiness.

You will collaborate with data scientists, domain experts, and technical teams to translate business needs into tangible data products, implement semantic models with ontology and knowledge graphs, and enforce data quality and

Qualifications

• Advanced degree in Engineering, Data Science, Life Sciences, Computer Science, or related field.
• 3+ years of data engineering experience, including data modeling and database design.
• Proficiency with Python, R, SQL, and cloud-based architectures such as AWS services, Snowflake, and Redshift.
• Experience with NoSQL and graph databases.
• Strong analytical and problem-solving skills.
• Strong stakeholder-management skills and ability to translate discussions into actionable requirements.
• Ability to drive multiple projects simultaneously.
• Strong organizational skills and adaptability.
• Preferred: experience in regulated data environments (CDISC, HL7, FHIR, OMOP, DICOM, or manufacturing/quality data standards).
• Preferred: familiarity with high-dimensional data (imaging, sensor data).
• Preferred: experience with MLOps and model deployment workflows.
• Preferred: knowledge of manufacturing systems, laboratory information systems, or industrial data systems.
• Preferred: experience with knowledge graph architectures.

Responsibilities

• Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing Therapeutics Development & Supply data.
• Create and optimize structured and unstructured data flows using Python, R, SQL, DBT, cloud services, and modern engineering tools.
• Develop and maintain TDS-specific data repositories and enterprise-level data models.
• Ensure data is structured, versioned, traceable, and semantically aligned for AI/ML readiness.
• Translate business needs into high-quality data products and engineering requirements with data scientists and domain experts.
• Implement semantic models and future-proof data architectures with ontology and knowledge graph teams.
• Define data quality and performance standards and KPIs for TDS data assets.
• Apply data versioning and lineage tracking for compliance, traceability, and audit readiness.
• Follow software development best practices, including code versioning, DevOps integration, and documentation.
• Engage stakeholders to understand requirements, design solutions, and drive adoption.
• Support multiple concurrent projects, manage priorities, and deliver business value across the TDS network.

Skills

Data Modeling

Database Design

Data Versioning

Data Lineage Tracking

MLOps

Graph Databases

NoSQL Databases

Data Quality Standards

Data Integration

Data Architecture

Python Programming

SQL Proficiency

Cloud-Based Architectures

Stakeholder Management

Education

Advanced degree in Engineering, Data Science, Life Sciences, Computer Science, or related field

Tools

AWS Services

Snowflake

Redshift

DBT

Ontology

Knowledge Graphs

DevOps Tools

Laboratory Information Systems

Manufacturing Systems

High-Dimensional Data

Job description

Jobtailor is seeking a data engineer to design and maintain scalable data pipelines for Therapeutics Development & Supply data. You will optimize data flows with Python, R, SQL, DBT, and cloud services, and develop enterprise-level data models aligned for AI/ML readiness.

You will collaborate with data scientists, domain experts, and technical teams to translate business needs into tangible data products, implement semantic models with ontology and knowledge graphs, and enforce data quality and