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Description

As a Level 5 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

Lead the design and implementation of complex data pipelines and ETL processes to support our analytical and operational needs.

Architect and develop scalable, high-performance data systems using cloud technologies and big data platforms.

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.

Mentor junior engineers and provide technical leadership on data engineering best practices and methodologies.

Evaluate and recommend new technologies and tools to enhance our data infrastructure capabilities.

Contribute to the development of data governance policies and procedures.

Troubleshoot and resolve complex data-related issues in production environments.

About the team

Have you ever ordered a product on Amazon and when that box with the smile arrives you wonder how it got to you so fast? Wondered where it came from and how much it would have cost Amazon? If so, the Amazon Global Supply Chain Optimization team (SCOT) is for you.

We build systems to peer into the future and estimate the distribution of tens of millions of products every week to Amazon’s warehouses in the most cost-effective way. On this team, the forecasts we generate and historical data we gather and transform drive automated downstream systems to make critical buying, labor planning, and inventory routing decisions world-wide. The forecasting platforms we are creating are being sought after by diverse business planning use cases, including unintegrated Amazon subsidiaries.

Basic Qualifications

- 3+ years of data engineering experience

- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience

- Knowledge of distributed systems as it pertains to data storage and computing

- Experience with data modeling, warehousing and building ETL pipelines

- Experience working on and delivering end to end projects independently

- Experience programming with at least one modern language such as C++, C#, Java, Python, Golang, PowerShell, Ruby

- Experience with Redshift, Oracle, NoSQL etc.

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)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.