AmazonPosted 1mo ago

Data Engineer II, ISS Central Science and Analytics

Data Engineer II, ISS Central Science and Analytics at Amazon scores 14 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.

IN, KA, Bengalurumidfull-time

AI in this role

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Come and be part of the International Seller Services (ISS) Central Analytics Data Engineering (DE) team and work on solving cutting edge problems!

We are a team of DEs who support Applied Scientists, Data Scientist, and Economists who experiment, research, and turn machine/deep learning and AI research into great products for our customers.

ISS is seeking a smart, highly-motivated, and experienced Data Engineer to join our team. In this role, you'll help us create the right Data and ML infrastructure.

As a Data Engineer, you will provide technical leadership, lead data engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective.
You are passionate about working with huge datasets and have experience with the organization and curation of data for analytics. You have a strategic and long term view on architecting advanced data eco systems.
You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications.

Key job responsibilities
In this role, you have the opportunity to:

Design, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.
Implement data ingestion routines using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation
Identify opportunities in existing data solutions for improvements

Basic qualifications

- 3+ years of data engineering experience
- 4+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines

Preferred qualifications

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
- Experience with Airflow, Step functions, any other orchestration frameworks.

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