Senior AWS Data Engineer for Scalable Pipelines

Amazon Inc.; Factoria (WA); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Job summary

Amazon Data Services, Inc. is seeking a data engineer to own and scale our data infrastructure across AWS services. You will design, build, and optimize data pipelines and storage solutions, partnering with scientists, engineers, and product teams to drive data-driven decisions.

You will work on large volumes of data, implement robust ETL processes, and mentor peers in best practices for data quality and reliability within a fast-paced environment.

Qualifications

• 3+ years of data engineering experience.
• Experience with data modeling, warehousing and ETL pipelines.
• Experience with AWS data technologies (Redshift, S3, Glue, EMR, Kinesis, Firehose, Lambda, IAM).
• Experience with non-relational databases/data stores.

Responsibilities

• Build and maintain the data infrastructure to answer questions with data using software engineering best practices.
• Define data engineering processes leveraging various AWS services to improve accessibility, redundancy, data integrity, cost and storage.
• Develop high-quality solutions for faster development of products/models in scalable formats.
• Collaborate with Research/Applied Scientists, Data Engineers, BI Engineers, Data Scientists, Business Analysts, and PMs to understand requirements and decisions.
• Interface with other data teams to extract, transform, and load data from diverse sources using AWS data technologies.
• Lead the technical design and implementation of the data infrastructure.
• Design and manage data audit, quality and reconciliation processes with stakeholders.

Skills

Data engineering

Data modeling

ETL pipelines

Warehousing

Tools

Redshift

S3

AWS Glue

EMR

Kinesis

Firehose

Lambda

IAM

Job description

Amazon Data Services, Inc. is seeking a data engineer to own and scale our data infrastructure across AWS services. You will design, build, and optimize data pipelines and storage solutions, partnering with scientists, engineers, and product teams to drive data-driven decisions.

You will work on large volumes of data, implement robust ETL processes, and mentor peers in best practices for data quality and reliability within a fast-paced environment.