Intern DDIT APD D&A Platform Automation Engineering
We couldn't confirm this posting on Novartis's site in our latest checks -- see current similar openings below.
About this opportunity
As a Platform Automation Engineering Intern, you will work on designing and implementing AI-powered and Agentic AI-driven automation solutions that simplify and accelerate platform engineering and data engineering activities across the enterprise data ecosystem. This will also help to simplify end-to-end onboarding process.
What You’ll DoValidate and test new capabilities across enterprise Data & Analytics platforms, ensuring scalability, reliability, and compliance with platform standards.Design and develop automation solutions to streamline end-to-end onboarding and provisioning processes for data and analytics platforms.Build intelligent deployment frameworks to automate Data Engineering pipeline promotion across environments while validating adherence to engineering best practices, security controls, and governance standards.Develop AI and Agentic AI-powered solutions for proactive platform monitoring, observability, anomaly detection, alerting, and operational optimisation.Collaborate with platform engineers, architects, and data engineers to identify automation opportunities and enhance the overall developer experience.What You’ll Learn· Enterprise-scale Data & Analytics platforms, including Lakehouse, Data Governance, Data Quality, Master Data Management, and Data Access Management solutions.· Practical application of AI, GenAI, and Agentic AI for platform operations, monitoring, automation, and engineering productivity.· Modern Platform Engineering and Data Engineering practices across cloud-native ecosystems.· Enterprise integration patterns, APIs, automation frameworks, and self-service platform capabilities.· Agile delivery methodologies and collaboration within globally distributed Data & Analytics teams.Who We’re Looking For· Currently pursuing a B.E./B.Tech degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, Electronics, or a related field.· Strong analytical thinking, problem-solving abilities, and a passion for technology and innovation.· Interest in AI, automation, cloud platforms, and modern Data & Analytics ecosystems.· Basic programming knowledge in Python, Java, or similar technologies, with an eagerness to learn new tools and frameworks.· Strong communication, collaboration, and stakeholder engagement skills.· Ability to work effectively in a fast-paced, agile, and team-oriented environment.· Participation in hackathons, research projects, innovation challenges, or open-source contributions is an added advantage.What We Offer· Hands-on experience with enterprise-scale Data & Analytics platforms used across a global organization.· Exposure to industry-leading technologies including Snowflake, Databricks, Collibra, Ataccama, Reltio, Immuta, and AI-powered platform services.· Practical experience in cloud platforms, APIs, automation frameworks, DevOps, Platform Engineering, and Data Engineering.· Opportunity to contribute to cutting-edge AI, GenAI, and Agentic AI initiatives with real business impact.· Mentorship from experienced leaders and experts in Data Architecture, Platform Engineering, Data Governance, and AI.· A collaborative, agile, and innovation-driven environment where you can develop skills and accelerate your professional growth.
Job details
How this role compares
Computed from every other active Manufacturing & CMC role in our database, not just this employer's listings.
We currently track 415 comparable Intern/Fellow/Postdoc Manufacturing & CMC roles across 59 biopharma companies.
Salary context
88 of 415 peers report a salary range (USD, annualized)
Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.
Where these roles are based
Top locations among the 415 comparable roles
+ 20 more countries
Seniority mix
415 of 415 peers have a known seniority level
Therapeutic area mix
6 of 415 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Currently open similar roles
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How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.