Data Engineer Job in Hyderabad at Novartis

Novartis is hiring for the role of Data Engineer!

Responsibilities of the Candidate:

• Collaborates with domain experts, data scientists, and other stakeholders to fulfill use-case-specific data needs.
• Designs, develops, tests, and maintains ETL processes and data pipelines to extract, prepare, and iterate data for analysis in close alignment with TA and 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 a culture of transparency and communication regarding data modifications and lineage for all stakeholders.
• Implements and advocates for data engineering best practices, ensuring ETL processes and data pipelines are efficient, well-documented, and well-tested.
• Plays a role in knowledge sharing across data42 and the wider data engineering community at Novartis.
• Ensures compliance with security and governance principles.

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 of statistics, with the 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 in 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.