Pay: Salary not listed in the saved posting
Work setup: Unconfirmed
Employment: Unconfirmed

What you’ll work on

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.

From the employer’s posting

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.

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.

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.

What you’ll bring

All qualifications

Core experience

7+ Years experience building modern data solutions using Snowflake, Structured Query Language, Python, Apache Spark, and cloud technologies.
Experience supporting Generative Artificial Intelligence, Retrieval-Augmented Generation, or artificial intelligence-driven automation solutions.
Strong expertise in extract, transform, load and extract, load, transform processes, data modelling, orchestration, and performance optimization.
Experience mentoring engineers and driving adoption of engineering best practices across teams.
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.

Qualification wording

7+ Years experience building modern data solutions using Snowflake, Structured Query Language, Python, Apache Spark, and cloud technologies.

Experience supporting Generative Artificial Intelligence, Retrieval-Augmented Generation, or artificial intelligence-driven automation solutions.

Strong expertise in extract, transform, load and extract, load, transform processes, data modelling, orchestration, and performance optimization.

Experience mentoring engineers and driving adoption of engineering best practices across teams.

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.

Tools in this posting

Python
Snowflake
Spark
SQL
AWS

Source

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.

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.

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

Skills Desired Analytics, Artificial Intelligence (AI), Data Engineering, Data Pipelines, Data Science, Emerging Technologies, Generative AI, Machine Learning (ML), Natural Language, Snowflake GenAI

- 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.

Job description

View original posting ↗

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.

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 diversityandincl.india@novartis.com 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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Source & posting history

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Source excerpts

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Pay: No pay amount identified in the saved description.
Location & working pattern: Hyderabad (Office)
Job Description Summary #LI-Hybrid Location: Hyderabad, India
Work authorization: No clear work-authorization passage found. Eligibility is unconfirmed.

Open source at novartis.wd3.myworkdayjobs.com ↗Read the full description ↓

Status in our records: Active
First seen by us: Sep 15, 2026
Recorded sightings: 13
Last seen by us: Oct 8, 2026

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