Amazon

Data Engineering Intern

InternshipIn OfficeChandigarh, Chandigarh4 months30K/mo1 openingImmediate / Rolling

About this internship

Amazon has an open Data Engineering Intern position in Chandigarh for motivated freshers and final-year students. You will work on live data engineering projects and finish with something you can genuinely talk about in interviews. About the role As a Data Engineering Intern at Amazon, your core…

Skills you'll use

PythonSQLApache AirflowSparkETL PipelinesData WarehousingdbtAWS / GCPData ModellingGit

What you'll do

Work on building pipelines and warehouse models the analytics team depends on alongside the core team
Apply Python, SQL, Apache Airflow, Spark to live, production-facing problems
Document your work clearly for reviewers and stakeholders
Participate in reviews and act on the feedback you receive
Collaborate across engineering, product, design or business as required
Follow the team's quality, testing and documentation standards

Who can apply

Pursuing or recently completed B.E./B.Tech/BCA/MCA — 2026 freshers & final-year students welcome
Working knowledge of Python, SQL, Apache Airflow (or a genuine willingness to learn them)
Strong fundamentals in your discipline and clear problem-solving ability
Care with detail and the discipline to document your work
Clear written and verbal communication in English
Based in or willing to work from Chandigarh, Chandigarh

Perks & benefits

Networking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentorLive project experience

Interview & selection process

4 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Practical assignment or case study with a short walkthrough
3Discussion with the hiring manager on the role and your fit
4HR discussion — stipend, start date, expectations and offer

About Amazon

Amazon operates in the technology & e-commerce sector and has an active presence in Chandigarh. Interns here are put on real work from the start, because the team's view is that the fastest way to learn a craft is to practise it under people who already do it well — not to watch it from a…

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