Data Infrastructure & Data Science Engineer

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com

Job Function:

R&D Product Development

Job Sub Function:

R&D Machine Learning

Job Category:

Scientific/Technology

All Job Posting Locations:

Yokneam, Haifa District, Israel

Job Description:

Key Responsibilities:

• Design, implement, and operate end-to-end data pipelines that automatically extract data from diverse CARTO backup sources, ensuring reliability, scalability, and robust error handling.

• Architect and maintain scalable data infrastructure, ensuring compatibility across CARTO versions and proactively managing migrations and enhancements driven by AI team requirements.

• Build and optimize NoSQL (MongoDB or equivalent) and relational databases to store data extracts, metadata, and snapshots, enabling efficient querying, lineage tracking, and auditability.

• Implement monitoring, alerting, and observability frameworks to guarantee 24/7 pipeline availability, with defined incident response and remediation playbooks.

• Ensure compliance with data governance, security, and regulatory standards (including GxP where applicable), implementing access controls, logging, and documentation.

• Collaborate with Data Scientists and AI researchers to design feature engineering workflows, ML-ready datasets, and support model deployment pipelines.

• Develop advanced data transformation processes to normalize and enrich data into AI-ready formats for training, evaluation, and production ML workflows.

• Perform exploratory data analysis, statistical modeling, and develop predictive insights to improve AI algorithms and product performance.

• Contribute to machine learning lifecycle by supporting model training, validation, and integration into production systems.

Qualifications and Experience:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field (Master’s preferred).

• 3+ years of professional experience in data engineering, data modeling, or software development (industry or military experience highly valued).

• Proven experience in:

• • Building and maintaining data pipelines for analytical and ML workloads.

  • Python for data processing, automation, and scripting.

  • NoSQL databases (MongoDB) and relational databases for performance optimization.

  • Cloud platforms (Microsoft Azure preferred), containerization (Docker), and version control (Git).

• Strong foundation in data science concepts, including:

• • Statistical analysis and hypothesis testing.

  • Feature engineering and data preprocessing for ML.

  • Familiarity with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

• Familiarity with data governance, privacy, and regulatory considerations; ability to apply GxP-related practices where applicable.

• Excellent analytical, problem-solving, and communication skills; ability to thrive in a collaborative, fast-paced environment.

Required Skills:

Preferred Skills:

Analytical Reasoning, Artificial Intelligence (AI), Cognitive Computing, Data Modeling, Data Savvy, Detail-Oriented, Execution Focus, Machine Learning (ML), Natural Language Processing (NLP), Persistence and Tenacity, Project Management, Research and Development, SAP Product Lifecycle Management, Science, Technology, Engineering, and Math (STEM) Application, Scientific Research, Scripting Languages, Technologically Savvy