Senior Data Engineer - Data Science Products

About the Role

Roles and Responsibilities:

1. Lead the design, development, and deployment of scalable, production-grade data pipelines for commercial AI products.
2. Manage technical delivery from vendor partners, ensuring high-quality output aligned with Novartis standards, timelines, and budgets.
3. Serve as a bridge between business stakeholders (global and country-level commercial teams) and engineering, translating business needs into actionable data solutions.
4. Integrate and harmonize complex data from multiple sources, including internal systems (Veeva, CRM, sales ops) and third-party providers.
5. Apply and promote data governance, lineage tracking, and data quality monitoring aligned to compliance needs
6. Recommend innovative data engineering solutions and best practices that enhance the performance and efficiency of the data infrastructure
7. Collaborate with AI/ML engineers to ensure data readiness for model training, scoring, and operationalization.
8. Guide and mentor junior data engineers while contributing to the growth of the commercial data engineering capability within Novartis.

Essential Requirements:

1. Bachelor’s or master’s degree in computer science, engineering, or related field.
2. 7+ years of experience in data engineering, including at least 2+ years in a leadership or delivery oversight role.
3. Strong hands-on experience with Python, SQL, Spark/PySpark, and tools like Databricks, Airflow, Snowflake, Azure Data Factory.
4. Demonstrated ability to manage vendor teams and ensure quality delivery across geographically distributed teams.
5. Strong communication and stakeholder management skills; experience working with commercial business leads in pharma or life sciences.
6. Basic understanding of pharmaceutical commercial data at both country and global levels, including CRM data, sales performance data, field force activity, and syndicated datasets.
7. Familiarity with privacy and compliance frameworks relevant to healthcare data (HIPAA, GDPR, GxP).
8. Experience working in Agile, cross-functional product teams.

Preferred Qualifications:

1. Direct experience in pharma commercial domains such as market access, promotional analytics, or omnichannel customer engagement.
2. Knowledge of HCP/HCO identity resolution, customer 360 strategies, or AI-based targeting and segmentation use cases.
3. Exposure to MLOps workflows and how data pipelines support AI product deployment at scale.

Division Operations

Business Unit CTS

Location India

Site Hyderabad (Office)

Functional Area Data and Digital

Job Type Full time

Employment Type Regular

Shift Work No