Principal Scientist, Data Science – R&D

Jobtailor; Spring House (PA); On-site; USD 90,000 - 130,000; Full time

Job summary

Jobtailor in Spring House, PA is seeking a data engineering professional to design, build, and maintain scalable data pipelines for Therapeutics Development & Supply data. You will create and optimize structured and unstructured data flows using Python, R, SQL, DBT, and cloud services, and develop enterprise data models.

You will collaborate with data scientists, domain experts, and technology teams to ensure AI/ML readiness, implement semantic models, and enforce data quality standards while

Qualifications

• Advanced degree in Engineering, Data Science, Life Sciences, or Computer Science.
• 3+ years of experience in data engineering, including data modeling and database design.
• Proficiency with Python, R, SQL, and cloud architectures such as AWS, Snowflake, and Redshift.
• Experience with NoSQL and graph databases.
• Strong analytical, problem-solving, and stakeholder-management skills.
• Ability to translate discussions into actionable requirements.
• Ability to drive multiple projects with strong organizational skills and adaptability.
• Preferred: experience with regulated data environments (CDISC, HL7, FHIR, OMOP, DICOM) and manufacturing/quality data standards; familiarity with high-dimensional data and 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, domain experts, and digital technology teams.
• Implement semantic models and future-proof data architectures with ontology and knowledge graph teams.
• Define data quality and performance standards and KPIs for accuracy, completeness, and consistency.
• 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 scientific, technical, and operations stakeholders to understand requirements, design solutions, and drive adoption.
• Support multiple concurrent projects and manage priorities across the TDS network.

Skills

Data Engineering

Python Programming

SQL Proficiency

Cloud-Based Architectures

Data Modeling

Data Versioning

Data Lineage Tracking

NoSQL Databases

Graph Databases

Data Quality Standards

AI/ML Readiness

Education

Advanced degree in Engineering

Data Science

Life Sciences

Computer Science

Tools

AWS Services

Snowflake

Redshift

DBT

DevOps Integration

Job description

• 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, domain experts, and digital technology teams
• Implement semantic models and future-proof data architectures with ontology and knowledge graph teams
• Define data quality and performance standards and KPIs for accuracy, completeness, and consistency
• 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 scientific, technical, and operations stakeholders to understand requirements, design solutions, and drive adoption
• Support multiple concurrent projects and manage priorities across the TDS network

Requirements

• Advanced degree in Engineering, Data Science, Life Sciences, Computer Science, or related field
• 3+ years of experience in data engineering, 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, problem-solving, and stakeholder-management skills
• Ability to translate discussions into actionable requirements
• Ability to drive multiple projects simultaneously with strong organizational skills and adaptability
• Preferred: experience with regulated or standards-driven data environments such as CDISC, HL7, FHIR, OMOP, DICOM, or manufacturing/quality data standards
• Preferred: familiarity with high-dimensional data such as imaging and sensor data
• Preferred: experience connecting to or feeding MLOps and model deployment workflows
• Preferred: knowledge of manufacturing systems, laboratory information systems, or industrial data systems
• Preferred: experience with knowledge graph architectures

Core Competencies

Demonstrates expertise in designing and maintaining scalable data pipelines, ensuring data quality and compliance while collaborating with cross-functional teams to deliver high-quality data products. Proficient in utilizing modern engineering tools and cloud architectures to support data-driven decision-making in Therapeutics Development & Supply.

Highest-signal resume keywords

• Data Engineering
• Python Programming
• SQL Proficiency
• Cloud-Based Architectures
• Data Modeling

ATS Optimization Keywords

Hard Skills

• Data Pipeline Design
• Data Integration
• Data Repository Development
• Data Versioning
• Data Lineage Tracking
• Database Design
• NoSQL Databases
• Graph Databases
• Data Quality Standards
• AI/ML Readiness

Soft Skills

• Analytical Skills
• Problem-Solving
• Stakeholder Management
• Organizational Skills
• Adaptability

Certifications & Qualifications

• Advanced Degree in Engineering
• Data Science
• Life Sciences
• Computer Science

Industry Keywords

• Therapeutics Development
• Regulated Data Environments
• CDISC
• HL7
• FHIR
• OMOP
• DICOM
• Manufacturing Standards
• Knowledge Graph Architectures
• High-Dimensional Data

Tools & Technologies

• AWS Services
• Snowflake
• Redshift
• DBT
• DevOps Integration