Data Engineer I, SPIV Data Engineering

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

Level's read on this job

Level rates this data engineer role Little AI ●○○○: aI is not part of the work.
Level classifies it as a junior role.
Level lists 20,000+ other open roles at Amazon.
The role was posted in the last few days.

AI in this role

Selling Partner Identity Verification is working to identify and prevent fraudulent behavior through all stages of a seller's lifecycle. We are seeking a skilled Data Engineer to join our team and help us build and manage the Data for the business domains within the Selling Partner Identity Verification space. As a Data Engineer, you will play a crucial role in designing, implementing, and maintaining our data infrastructure and pipelines. You will work closely with cross-functional teams to deliver scalable and efficient data solutions that drive business value.

Key job responsibilities
You will design and develop scalable, high-performance data systems using medallion architecture.

You are expected to collaborate with data scientists, analysts, and business stakeholders to understand data requirements and implement appropriate solutions.

Optimize data storage and retrieval systems for improved performance and cost-effectiveness.

Implement data quality checks and monitoring systems to ensure data integrity and reliability.

A day in the life
A Data Engineer I on SPIV starts their day by syncing with the team on data pipeline status, checking for any overnight failures in ETL jobs processing seller identity verification data. They collaborate with data scientists to understand new fraud detection requirements, then design and implement scalable data models using medallion architecture to support these use cases.

About the team
SPIV Data Engineering builds the data backbone for Selling Partner Identity Verification - preventing fraud across the seller lifecycle. Our Northstar is to build business domain datasets with data as product mental model. We're a collaborative team that values ownership, technical rigor, and shipping solutions that matter. You'll work with data scientists, analysts, and business teams. We emphasize learning, code quality, and building infrastructure that scales.

Basic qualifications

- 1+ years of data engineering experience
- Experience with SQL
- 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.

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How we rate this

Data Engineer I, SPIV Data Engineering at Amazon rates 24 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.