Data Engineer Intern

Amazon, a global leader in e‑commerce, cloud computing, digital streaming and artificial intelligence, has built a reputation for relentless customer obsession and innovation. With a presence in more than 20 countries and a workforce of over a million, Amazon offers a fast‑paced environment where ideas are turned into products that impact billions of users. The company’s data ecosystem powers everything from recommendation engines to supply‑chain optimization, making data engineering a core pillar of its business strategy.

Interns at Amazon get a front‑row seat to this data‑driven culture, working alongside seasoned engineers and product managers to solve real‑world problems.

The Data Engineer Intern role for the 2027 batch is designed to give fresh talent hands‑on experience in building and maintaining large‑scale data pipelines. You will collaborate with business analysts, software developers, and senior data engineers to ingest, transform, and store data from diverse sources. The internship is full‑time and spans a typical 12‑week period, during which you will be expected to contribute to production‑grade solutions and present your work to cross‑functional stakeholders.

Key Responsibilities

• Design, develop, and support analytical data platform solutions that enable data‑driven decision making.
• Create and maintain data schemas, and manage internal data warehouses using SQL and NoSQL databases.
• Build ETL pipelines that extract, transform, and load data from various sources using AWS services such as EMR, Redshift, and Glue.
• Work with data‑lake components like Amazon S3 and Hadoop to store and process massive datasets.
• Implement and optimize big‑data processing jobs using Spark, Hive, and Impala on Hadoop clusters.
• Explore and adopt new AWS technologies (Lambda, Athena, etc.) to improve efficiency and add capabilities.
• Develop dashboards, reports, and metrics that surface actionable insights for business teams.
• Ensure data quality, integrity, and documentation throughout the pipeline lifecycle.
• Participate in code reviews, adhere to software‑engineering best practices, and contribute to agile sprint activities.
• Continuously learn and share knowledge about emerging data‑engineering tools and practices.

Tech Stack: Python, SQL, PostgreSQL/MySQL, DynamoDB, Amazon S3, EMR, Redshift, Glue, Lambda, Hadoop, Spark, Hive, Impala, Airflow (optional), Git, Docker.

Growth Path: Successful interns often receive full‑time offers as Data Engineers or Software Development Engineers, with clear career ladders that lead to senior, principal, and leadership roles within Amazon’s data organization.

Why Join Amazon?: You will work on high‑impact projects that scale to millions of users, gain exposure to cutting‑edge cloud technologies, and develop a deep understanding of end‑to‑end data pipelines. The internship also provides mentorship from senior engineers, a collaborative culture, and the opportunity to turn data insights into tangible business outcomes.