Senior Data Engineer

As a Senior Data Engineer at Novartis, you will play a pivotal role within the Data & Digital Commercial organization, leading the technical foundation of AI-powered commercial solutions. Your contributions will be instrumental in driving more effective engagement, access, and performance both globally and within local markets. Your responsibilities will include designing, developing, and deploying scalable, production-grade data pipelines for commercial AI products. You will oversee the technical delivery from vendor partners, ensuring high-quality output that aligns with Novartis standards, timelines, and budgets. Acting as a liaison between business stakeholders and engineering teams, you will translate business requirements into actionable data solutions. In this role, you will integrate and harmonize complex data from various sources, including internal systems and third-party providers. Upholding data governance, lineage tracking, and data quality monitoring will be essential to ensure compliance requirements are met. You will also be expected to recommend innovative data engineering solutions that enhance the performance and efficiency of the data infrastructure. Collaboration with AI/ML engineers to ensure data readiness for model training, scoring, and operationalization will be a key aspect of your role. Additionally, you will guide and mentor junior data engineers, contributing to the growth of the commercial data engineering capability within Novartis. To qualify for this position, you should hold a Bachelor's or Master's degree in computer science, engineering, or a related field. With at least 7 years of experience in data engineering, including 2 years in a leadership or delivery oversight role, you should possess strong expertise in Python, SQL, Spark/PySpark, and tools like Databricks, Airflow, Snowflake, and Azure Data Factory. Your ability to manage vendor teams, communicate effectively, and work collaboratively with commercial business leads in pharma or life sciences will be crucial. Experience with pharmaceutical commercial data, knowledge of privacy and compliance frameworks relevant to healthcare data, and familiarity with Agile methodologies are highly desirable. Direct experience in pharma commercial domains, exposure to MLOps workflows, and an understanding of AI-based targeting and segmentation use cases are considered advantageous qualifications. Novartis is dedicated to fostering a diverse and inclusive work environment that reflects the patients and communities it serves. If you require accommodation due to a medical condition or disability, please reach out to the provided contact information for assistance. Join Novartis in reimagining medicine and creating a brighter future together.,