Amazon

Data Engineer I

Bengaluru · On-site · 1+ yrs · Junior · Full-time

  • sql
  • aws
  • python
  • hadoop
  • hive
  • spark
  • emr
  • etl

Data Engineer I at Amazon Bengaluru building BI solutions with AWS, SQL, and big data technologies for data ingestion and warehousing.

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Posted 19 Oct 2026 · found on Amazon's own careers page

Interview prep: questions this posting points to

Written from 8 current Data Engineering postings on Amazon's own careers page — not questions Amazon has asked.

  1. Walk me through how you would design an ETL pipeline on AWS Glue and Redshift that consolidates finance data from 11 countries into a single unified dataset tracking 500+ operational and cost metrics at daily granularity. How would you structure it so that a new country can be onboarded without rewriting the pipeline?
    From the posting: “build and scale a unified data platform that supports over 100 active finance users across 11 countries... tracks 500+ operational and cost metrics at daily granularity”
  2. It's the morning before a weekly business review and the finance team's cost-performance dashboard is showing numbers that don't reconcile between finance, stores, and operations datasets. Walk me through how you'd triage this.
    From the posting: “collaborating with finance analysts to reconcile discrepancies between finance, stores, and operations datasets”
  3. These teams are actively migrating legacy systems to AWS and consolidating data from 11 countries and 100+ finance users. Tell me about a time you had to manage a complex data migration while keeping the old system running. What went wrong, and how did you handle it?
    From the posting: “the team is revamping the legacy datasets, dashboards and processes and is actively migrating to a new AWS-based infrastructure”
See all 65 questions More on this prep
Read the full job description

Do you have the technical skill to build BI solutions that process billions of rows a day using AWS technologies? Do you want to create next-generation tools for intuitive data access? Do you wake up in the middle of the night with new ideas that will benefit your customers? Are you persistent in bringing your ideas to fruition?

First things first, you know SQL and data modelling like the back of your hand. You also need to know Big Data and MPP systems. You have a history of coming up with innovative solutions to complex technical problems. You are a quick and willing learner of new technologies and have examples to prove your aptitude.

You are not tool-centric; you determine what technology works best for the problem at hand and apply it accordingly. You can explain complex concepts to your non-technical customers in simple terms. Key job responsibilities - Work with SDE teams and business stakeholders to understand data requirements and design data ingress flow for team - Lead the design, model, and implementation of large, evolving, structured, semi-structured and unstructured datasets - Evaluate and implement efficient distributed storage and query techniques - Interact and integrate with internal and external teams and systems to extract, transform, and load data from a wide variety of sources - Implement robust and maintainable code with clear and maintained documentation - Implement test automation on code implemented through unit testing and integration testing - Work in a tech stack which is a mix of NAWS services and legacy ETL tools within Amazon

About the team

Data Insights, Metrics & Reporting team (DIMR) is the central data engineering team in Amazon Warehousing & Distribution org which is responsible for 4 things mainly - - Building and maintaining data engineering and reporting infrastructure using NAWS to support internal/external data use-cases. - Building data ingestions pipelines from any kind of upstream data sources which include (but not limited to) real time event streaming services, data lakes, manual file uploads, etc. - Building mechanisms to vend data to internal team members or external sellers with right data handling techniques in place. - Build robust data mart to support diverse use-cases powered by GenAI tool.

Basic qualifications

- 1+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell)

Preferred qualifications

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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