Job Description Summary

Job Description

Major Accountabilities 

• Design, build, and optimize scalable batch, streaming, CDC, and event-driven data pipelines using modern data engineering best practices and production-grade Python and SQL.
• Architect secure, resilient, high-performance data platforms and translate business and technical requirements into scalable cloud-based solutions.
• Lead hands-on development and optimization of Databricks, Apache Spark, Delta Lake, and Lakehouse solutions, ensuring reliability, performance, and cost efficiency.
• Design and implement Snowflake data engineering solutions, including ingestion, transformation, governance, orchestration, and secure data consumption patterns.
• Engineer enterprise data platforms on AWS, leveraging cloud-native services to deliver secure, automated, observable, and highly available data solutions.
• Develop reusable integration frameworks, APIs, CDC processes, and connectivity patterns across enterprise applications, SaaS platforms, governance tools, ERP, and CRM systems.
• Build AI-ready data foundations, including RAG pipelines, vector retrieval, context engineering, and agentic workflows, enabling enterprise AI and GenAI use cases.
• Drive engineering excellence through CI/CD, Infrastructure as Code, security-by-design, observability, governance, mentoring, and end-to-end ownership of data products and platform capabilities.

Minimum Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, Information Technology, or a related discipline, or equivalent practical experience.
• 12+ years of experience in software engineering and/or data engineering with proven delivery of large-scale production data platforms.
• Advanced hands-on expertise in Python, SQL, data modeling, ETL/ELT, CDC, batch, streaming, and event-driven architectures.
• Strong experience with Apache Spark (PySpark), distributed data processing, performance tuning, and troubleshooting.
• Proven hands-on experience with Databricks, Delta Lake, and Snowflake in enterprise-scale environments.
• Deep knowledge of AWS cloud services, cloud-native data architectures, security, observability, Infrastructure as Code, and automation.
• Experience implementing CI/CD pipelines, automated testing, monitoring, governance, data quality, security controls, and operational support practices.
• Practical exposure to Generative AI technologies, including RAG architectures, embeddings, vector search, LLM integration, context engineering, and agentic workflows.
• Strong understanding of enterprise integration patterns, APIs, SaaS integrations, metadata management, lineage, data governance, and access control frameworks.
• Excellent stakeholder management, communication, mentoring, problem-solving, and delivery leadership skills with a highly hands-on engineering mindset.

Why Novartis?

Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us!
Learn more here:

https://www.novartis.com/about/strategy/people-and-culture

Commitment to Diversity and Inclusion:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.
Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here:
https://talentnetwork.novartis.com/network

Skills Desired