Job Description Summary

The Data Engineering Lead guides and drives execution of the development of robust data assets from both internal and external sources to support data interrogation, driving re-search and development efforts, and external collaborations in the Neuroscience development area. By collaborating with our quantitative science community, TSC and Statistical Programming colleagues, IT, QA, BR data science teams, and vendors, the Data Engineering Lead ensures the delivery of fit-for-purpose and high-quality data assets, automation pipelines and associated technical and quality documentation, facilitating scientific advancements in drug development in Neuroscience.

Job Description

Key Responsibilities:

• Develops data pipelines and IT infrastructure solutions to enable Quantitative Sciences to utilize high quality datasets to make quantitative decisions at trial and/or project level activities:
• Provides technical leadership for data engineering projects:
• Builds strong collaborative working relationships and communicates effectively with Quantitative Science partners along with clinical teams to promote a greater mindset where associates may leverage each other’s skills in an open and transparent manner.
• Plays a lead role in agile engineering and consulting, providing guidance on for complex data and unplanned data challenges.
• Ensure all data engineering processes are well-documented in compliance with legal and regulatory requirements, as well as data security and privacy best practices.
• Helps establish and strengthen the link between Novartis and the external data engineering community through open-source contributions and publications, as well as through external congresses, conferences, and other scientific workshops and meetings.
• Encourages a culture of continuous learning, constructive collaboration, and innovation within the team.

Experience/Professional requirement:

• MSc or PhD in Computer Science/Engineering, Data Sciences, Bioinformatics, Biostatistics or any other computational quantitative science

• Minimum of 4-6 years of developing data pipelines & data infrastructure, ideally within a drug development or life sciences context
• Expert in software / data engineering practices (including versioning, release management, deployment of datasets, agile & related software tools).
• Strong software development skills in R and Python, SQL.
• Strong working knowledge of at least one large-scale data processing technology (e.g. High-performance computing, distributed computing), databases and underlying technology (cloud or on-prem environments, containerization, distributed storage & databases)
• Strong interpersonal and communication skills (verbal and written) effectively bridging scientific and business needs; experience working in a matrix environment
• Proven record of delivering high-quality results in quantitative sciences and/or a solid publication track record

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve

Skills Desired

Apache Spark, Artificial Intelligence (AI), Big Data, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Machine Learning (Ml), Master Data Management, Python (Programming Language), R (Programming Language), Statistical Analysis