Data Engineer I

Amazon is hiring a Data Engineer I in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this data engineer role is Little AI ●○○○: aI is not part of the work.
The posting mentions AWS, SQL and Hiveql among its tools and skills.
Level classes it as a junior role.
Amazon has 21,000+ other open roles on Level.
Posted within the past week.

AI in this role

Build and maintain data engineering infrastructure and ETL pipelines using AWS technologies to support internal and external data use-cases.

awssqlhiveqletl

data-engineeringdata-modelingbig-dataetl-pipelines

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.

How we rate this

Data Engineer I at Amazon rates 35 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Engineer I is an open job at Amazon.
Level rates this role AI Level 1 of 4: Little AI.
The role is based in IN, KA, Bengaluru.
The job was posted on October 19, 2026.
Seniority: junior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data EngineeringData ModelingBig DataETL PipelinesAWSSQLHiveqlETL

Also common in data engineer jobs at this level

Azure Databricks Airflow Google Cloud Snowflake Java

Pay

Typical data engineer job: $150k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where data modeling was part of your work. What did you do?
Tell me about a project where big data was part of your work. What did you do?
Tell me about a project where etl pipelines was part of your work. What did you do?
Walk me through how you've used AWS in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Data Engineering, Data Modeling, Big Data, ETL Pipelines, and AWS. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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