Sobre este puesto de Senior Data Engineer – Data & AI Platforms en Novartis
Novartis · Presencial · Hyderabad (Office)
Job Description Summary
#LI-HybridLocation: Hyderabad, India
Number of Openings: 4
Relocation Support: Yes
Imagine building the data foundations that power the next generation of artificial intelligence and digital innovation. As a Senior Data Engineer – Data & AI Platforms, you will play a pivotal role in designing and scaling enterprise-grade data platforms that enable advanced analytics, artificial intelligence, and business-critical insights. Working across cloud technologies, Snowflake, distributed processing, governance, and AI-enabled solutions, you'll transform complex data challenges into secure, high-performing, and reusable products. If you're passionate about modern data engineering, eager to work with cutting-edge technologies, and motivated by delivering real business impact, this is an opportunity to shape the future of data and AI at scale.
Job Description
Key Responsibilities
- Design, build, and optimize scalable data pipelines using Amazon Web Services, Snowflake, Python, and Apache Spark.
- Develop batch, event-driven, and distributed data processing solutions for enterprise-wide data products.
- Deliver reliable, high-performance data platforms that support analytics, artificial intelligence, and business insights.
- Implement data quality frameworks, monitoring, error handling, metadata management, and lineage capabilities.
- Enable strong governance through data cataloging, access controls, auditability, and compliance standards.
- Support artificial intelligence and machine learning initiatives through feature engineering and data pipeline development.
- Build reusable data assets and automation solutions that accelerate delivery and operational efficiency.
- Apply engineering best practices including version control, continuous integration, automated testing, and code reviews.
- Collaborate with product owners, architects, business stakeholders, and platform teams to deliver trusted data solutions.
- Mentor engineers and contribute to engineering standards, innovation, and technical excellence across the team.
Essential Requirements
- 7+ Years experience building modern data solutions using Snowflake, Structured Query Language, Python, Apache Spark, and cloud technologies.
- Strong expertise in extract, transform, load and extract, load, transform processes, data modelling, orchestration, and performance optimization.
- Hands-on experience with Amazon Web Services services including Glue, Simple Storage Service, Lambda, Step Functions, and workflow orchestration tools.
- Experience implementing data governance, metadata management, lineage, compliance, and security controls using governance platforms.
- Familiarity with artificial intelligence and machine learning technologies, including Generative Artificial Intelligence, machine learning operations, and automation concepts.
- Experience applying continuous integration, continuous delivery, automated testing, version control, and cloud-native engineering practices.
Desirable Requirements
- Experience supporting Generative Artificial Intelligence, Retrieval-Augmented Generation, or artificial intelligence-driven automation solutions.
- Experience mentoring engineers and driving adoption of engineering best practices across teams.
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.
Accessibility and accommodation
Novartis is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to perform the essential functions of a position, please send an e-mail to [email protected] and let us know the nature of your request and your contact information. Please include the job requisition number in your message
Skills Desired
Analytics, Artificial Intelligence (AI), Data Engineering, Data Pipelines, Data Science, Emerging Technologies, Generative AI, Machine Learning (ML), Natural Language, Snowflake GenAI
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