Principal Data Engineer, Biologics Discovery

Johnson & Johnson

. Design and deliver AI-ready discovery data products for ML, AI, and insight generation across Biologics Discovery .

Posted 9/18/2026full-timeSpring House • New Jersey • United StatesLead💰 $117,000 - $201,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in designing and delivering AI-ready data products, with a strong focus on data integration, transformation, and analytics within the life sciences domain. Proficient in applying FAIR data principles and leading cross-functional technical initiatives to establish data standards and best practices.

Highest-signal resume keywords

Data Product DesignPython ProficiencySQL ProficiencyCloud Data PlatformsFAIR Data Principles

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingAnalytics-Ready DatasetsData IntegrationData TransformationData Quality StandardsMetadata ManagementData LineageData ProvenanceMachine Learning SupportTechnical Leadership

Soft Skills

Strong Communication SkillsCross-Functional Leadership

Tools & Technologies

SnowflakeAWSAzureBigQuery

Industry Keywords

Biologics DiscoveryPharmaceuticalBiotechnologyLife SciencesData Standards

Tech Stack

Tools & technologies

AWSAzureBigQueryCloudPythonSQL

About the role

Key responsibilities & impact

Design and deliver AI-ready discovery data products for ML, AI, and insight generation across Biologics Discovery
Define and lead scalable integration requirements, transformation patterns, and data schemas
Enable discovery data acquisition, harmonization, and downstream analytics across systems
Translate scientific and analytical requirements into data product specifications, data contracts, acceptance criteria, and delivery requirements
Define access and data consumption patterns for analytics, modeling, and agentic AI workflows
Catalog discovery instruments, data types, and data sources to inform prioritization and integration approaches
Establish and drive adoption of standards and best practices for data quality, provenance, lineage, reproducibility, metadata, and documentation
Partner with ontology, data architecture, platform, and AI teams to connect and improve discovery data products
Apply FAIR data principles to make data products reusable, scalable, and interoperable
Serve as a thought leader in scientific data architecture, harmonization, and AI-ready data practices

Requirements

What you’ll need

Degree in Computer Science, Data Science, Engineering, or a related computational field
8+ years of experience with a Bachelor's degree, 5+ years with a Master's degree, or 3+ years with a Ph.D.
Experience designing and delivering data products, data models, and analytics-ready datasets within pharmaceutical, biotechnology, or life sciences organizations
Deep proficiency in Python and SQL
Hands-on experience designing and implementing reusable and scalable data assets on cloud data platforms such as Snowflake, AWS, Azure, or BigQuery
Experience supporting analytics, machine learning, and AI-driven workflows
Experience applying FAIR data principles, metadata management, controlled vocabularies, data lineage, and provenance practices in scientific data environments
Demonstrated technical leadership through architecture reviews, mentorship, code reviews, or leadership of complex technical initiatives
Ability to lead complex cross-functional technical initiatives and establish data standards across multiple stakeholder groups
Strong communication skills and seniority to represent the team in architecture, data, and strategy forums

Benefits

Comp & perks

Annual performance bonus eligibility
Medical, dental, and 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