Senior Data Engineer – Data & AI Platforms
- Nivel de experiencia
- Senior
- Tipo de empleo
- Tiempo completo
- Experiencia laboral
- 7+ years
- Especialización
- Machine learning & AI
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.
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.
- 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. 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
Key skills
- Snowflake
- Data Engineering
- AWS
- Python
- Apache Spark
- Machine Learning
- CI/CD
- Test Automation
- Data Modeling
- Data Science
- Generative AI
Benefits & perks
- Remote friendly
Job Description Summary
#LI-Hybrid
Location: 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.
