Περίληψη
About the Role
Your responsibilities will include, but are not limited to:
- 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.
Minimum Requirements:
- 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.
Desirable additional skills in two or more of the following areas:
- 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.
Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture
Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network
Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.
![A female Novartis scientist wearing a white lab coat and glasses, smiles in front of laboratory equipment. A female Novartis scientist wearing a white lab coat and glasses, smiles in front of laboratory equipment.](/themes/custom/nvs_arctic/patterns/images/careers-default-image.webp)