Data Engineer - data42

The Data Engineer will work alongside data scientists and domain experts to enable teams to answering scientific questions using multi-modal data on the data42 platform. They will be involved in gathering use-case requirements, performing engineering activities for data services, building ETL processes/data pipelines in quick iterations to deliver data ready for analysis. The Data Engineer will integrate data engineering best practices and data quality checks and seek to continuously optimize efficiency.

• Collaborates with domain experts, data scientists and other stakeholders to fulfil use-case specific data needs.
• Designs, develops, tests, and maintains ETL processes/data pipelines to extract, prepare and iterate data for analysis in close alignment with TA / DA scientific leads and data scientists.
• Implements and maintains data checks to ensure accurate and high quality-data in close collaboration with domain experts.
• Identifies and rectifies data inconsistencies and irregularities.
• Promotes culture of transparency and communication regarding data modifications and lineage to all stakeholders.
• Implements and advocates for data engineering best practices, ensuring ETL processes/data pipelines are efficient, well-documented and well-tested.
• Plays a role in knowledge sharing across data42 and wider data engineering community at Novartis.
• Ensures compliance with Security and Governance Principles.

• Bachelor s degree in computer science or other quantitative field (Mathematics, Statistics, Physics, Engineering, etc.) or equivalent practical experience.
• Proven experience as a data engineer, data wrangler or a similar role.
• Exceptional programming skills with expertise in Python, R and Spark.
• Experience and familiarity with a variety of data types, including but not limited to images, tabular, unstructured, and text.
• Experience in scalable data processing engines, data ingestion, extraction and modeling.
• Proficient knowledge in statistics, with an ability to assess data quality, errors, inconsistencies, etc.
• Good knowledge of data engineering best practices Excellent communication and stakeholder management skills.
• Demonstrated ability to work independently and as part of global Agile teams.

• Hands on experience on Palantir Foundry (Code Repository, Code Workbook, Contour, Data Lineage, etc.)
• Knowledge of CDISC data standards (SDTM, ADaM)
• Experience using AI (eg: GenAI/LLMs) for data wrangling.
• Experience with pooling of clinical trial data.
• High-level understanding of the drug discovery and development process.

Algorithms, Computer Programming, Computer Science, Computer Vision, Data Science, People Management, R&D (Research And Development), Waterfall Project Management