Lead data engineering efforts to support commercial solutions in healthcare, ensuring data quality and scalability using cloud-based technologies.

About the Company

Novartis is a global healthcare company dedicated to improving patients' lives through innovative science and technology. With a presence in over 140 countries, Novartis focuses on developing breakthrough medicines and digital solutions that address some of the world's most challenging health issues. The company values diversity, inclusion, and collaboration, fostering an environment where employees can thrive and make a meaningful impact.

Role Overview

As a Data Steward at Novartis, you will play a crucial role in shaping the future of data engineering within the life sciences sector. This position focuses on leading data engineering efforts, supporting data science and reporting & analytics teams to build scalable commercial solutions. You will drive automation, quality, and efficiency in cloud-based data integration, collaborating with cross-functional teams to deliver actionable insights for medical and sales representatives. This is an opportunity to contribute to global healthcare through cutting-edge data practices.

Key Responsibilities

• Design scalable data ingestion and integration solutions to support data products for data science and reporting & analytics.
• Ensure data quality by applying business and technical rules throughout its lifecycle.
• Identify and implement automation opportunities to streamline data processes.
• Build data pipelines using Python and CI/CD workflows for seamless data integration.
• Collaborate with solution architects and vendors to align with best practices.
• Apply data management principles including modeling, harmonization, and ontology standards.
• Manage metadata effectively and leverage enterprise ontology tools.
• Ensure adherence to FAIR data principles across applicable projects.
• Conduct feasibility assessments and define project requirements with stakeholders.
• Support end-user training and promote self-service data capabilities.

Tech Stack

• Programming Languages: Python, PySpark, R
• Databases: Oracle, MS SQL Server, Snowflake (Cloud-based)
• ETL & BI Tools: Alteryx, Power BI
• Cloud Platforms: AWS
• DevOps & CI/CD: CI/CD workflows
• Data Management: Data modeling, ontology, metadata management, FAIR data principles
• Methodologies: Agile
• Additional: Data science concepts, commercial experience in healthcare/life sciences

University degree in Informatics, Computer Sciences, Life Sciences, or a related field. 1-4 years of experience in data engineering with understanding of healthcare or life sciences. Proven expertise in Python, PySpark, and R for ETL and BI development. Strong experience with DevOps, AWS cloud data integration, and third-party ingestion tools. Proficiency in SQL for relational databases like Oracle and MS SQL Server. Proficiency in Cloud-based databases like Snowflake is a plus. Hands-on experience with ETL tools like Alteryx and BI platforms like Power BI. Solid understanding of data architecture, modeling, and analytics concepts. Familiarity with Agile methodologies in global project environments. Understanding of data science concepts is a plus.

Health insurance, retirement plans, paid time off, professional development opportunities, and a collaborative work environment.