AWS Data Engineer II — Data Lake & Pipelines

Amazon Web Services (AWS); Seattle (WA); On-site; USD 132,000 - 179,000; Full time

Job summary

Amazon Data Services, Inc. in Seattle, WA is seeking a Data Engineer to support data center construction with a serverless, AWS-based data lake and warehouse.

You will build ETL and analytics solutions for internal customers, using Python, Spark, and AWS services to enable data-driven decisions across thousands of variables. You will collaborate with diverse teams, automate deployments, ensure data quality and governance, and continuously optimize pipelines while staying current with new

Qualifications

• Bachelor's degree in a technical field or equivalent experience.
• 3+ years of data engineering experience.
• Experience with data modeling, warehousing, and ETL pipelines.
• Proficiency in SQL and data manipulation.
• Knowledge of distributed systems for data storage and processing.
• Experience with batch and streaming data architectures.
• Experience in at least one modern programming language (Python, Java, Scala, or NodeJS).
• Experience with Apache Spark / EMR.

Responsibilities

• Design scalable, fault-tolerant data pipelines using AWS and internal tools.
• Collaborate with BIEs, Data Scientists, PMs, and SDEs to deliver data solutions.
• Automate deployment with CI/CD pipelines and maintain data infrastructure.
• Ensure data quality through validation, cleansing, and deduplication.
• Implement data governance, access control, encryption, and retention policies.
• Improve and optimize data pipelines and infrastructure, adopting new technologies.

Skills

Python

SQL

Data modeling

ETL pipelines

Distributed systems

Kinesis

Cloud data engineering

Education

Bachelor's degree

3+ years data engineering experience

Tools

AWS Redshift

AWS S3

AWS Glue

EMR

Kinesis

Athena

Lambda

Airflow

Spark

Job description

Amazon Data Services, Inc. in Seattle, WA is seeking a Data Engineer to support data center construction with a serverless, AWS-based data lake and warehouse.

You will build ETL and analytics solutions for internal customers, using Python, Spark, and AWS services to enable data-driven decisions across thousands of variables. You will collaborate with diverse teams, automate deployments, ensure data quality and governance, and continuously optimize pipelines while staying current with new