Principal Developer, Oncology Data – AI Systems

Johnson & Johnson

. Partner with Oncology R&D and Data Science stakeholders to identify, prioritize, and deliver data, AI/ML, and GenAI use cases .

Posted 10/1/2026full-timeUnited StatesLead💰 $117,000 - $201,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering, including the design and management of data products, while leveraging Python, R, SQL, and AWS technologies to create AI-ready datasets. Proven ability to lead cross-functional teams and implement data governance frameworks in the healthcare domain.

Highest-signal resume keywords

Data EngineeringPython ProgrammingAWS Data PlatformsData GovernanceHealthcare Data Standards

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingSchema DesignDatabase ArchitectureETL/ELT DevelopmentData Pipeline OptimizationData Quality ControlAutomated MonitoringKPI Performance MeasurementMulti-Modal Data IntegrationAI/ML Use Case Development

Soft Skills

Analytical SkillsProblem-SolvingStakeholder ManagementRequirements DiscoveryProject Management

Tools & Technologies

PythonRSQLAWS RedshiftAWS GlueAWS LambdaNoSQL TechnologiesGraph Data TechnologiesMLOpsGenAI

Industry Keywords

Oncology R&DClinical TrialsGenomicsFAIR Data PrinciplesCDISCHL7FHIRSNOMED CTOMOPDICOM

Tech Stack

Tools & technologies

Amazon RedshiftAWSCloudETLNoSQLPythonSQL

About the role

Key responsibilities & impact

Partner with Oncology R&D and Data Science stakeholders to identify, prioritize, and deliver data, AI/ML, and GenAI use cases
Own the end-to-end design, build, and lifecycle management of Oncology R&D data products
Define requirements, architecture, ETL/ELT development, documentation, and operational support
Integrate and harmonize multi-modal R&D data across biomarker labs, translational platforms, clinical trials, real-world data/evidence, genomics/omics, and pre-clinical research systems
Create trusted, reusable, AI-ready datasets
Co-develop an AI-ready data ecosystem with Data Product Engineers, Data Scientists, Knowledge Graph Engineers, Enterprise Architecture, and IT
Translate scientific, clinical, and operational needs into scalable engineering solutions
Design and optimize structured and unstructured data pipelines using Python, R, SQL, AWS, and other relevant technologies
Implement data quality and reliability controls, automated monitoring, and KPI-driven performance measurement
Establish data governance foundations, including data lineage, metadata, versioning, FAIR data principles, and compliance workflows
Support Oncology R&D data-driven decision-making and downstream analytics/model development

Requirements

What you’ll need

Bachelor’s Degree in Computer Science, Engineering, Life Sciences, or another relevant field
5+ years of experience in data engineering, including data modeling, schema design, and database architecture
Healthcare industry experience preferred
Proficiency in Python, R, and SQL for data processing, transformation, and automation across large-scale datasets
Hands-on experience designing and operating cloud-based data platforms, preferably AWS (Redshift, FSx, Glue, Lambda) or equivalent services
Experience with relational, NoSQL/unstructured, and graph data technologies
Strong analytical and problem-solving skills, including troubleshooting complex data pipeline, quality, and performance issues in production
Ability to lead cross-functional delivery and continuous improvement initiatives with multidisciplinary, distributed teams
Experience coordinating with external vendors/partners
Stakeholder management, requirements discovery, business analysis, and planning skills
Ability to translate conversations into user stories, engineering requirements, and executable delivery plans
Ability to manage multiple concurrent projects and prioritize work
Willingness to conduct periodic travel (less than 15% of time)
Advanced degree preferred
Healthcare data standards experience preferred, including CDISC, HL7, FHIR, SNOMED CT, OMOP, or DICOM
Exposure to high-dimensional data technologies, including imaging, preferred
Familiarity with MLOps and GenAI model deployment preferred

Benefits

Comp & perks

Annual performance bonus
Medical insurance
Dental insurance
Vision insurance
Life insurance
Short- and long-term disability insurance
Business accident insurance
Group legal insurance
Pension plan
401(k) savings plan
Vacation — up to 120 hours per calendar year
Sick time — up to 40 hours per calendar year
Holiday pay, including Floating Holidays — up to 13 days per calendar year
Work, Personal and Family Time — up to 40 hours per calendar year
Inclusive interview process and disability accommodations