AI-Driven Data Engineer for Scalable Pipelines

Amazon Inc.; Bellevue (WA); On-site; USD 101,000 - 160,000; Full time

Benefits offered by this job

Sign-on payments

Restricted stock units (RSUs)

Health insurance

EAP and Mental Health Support

Flexible Spending Accounts

Parental leave

Job summary

Amazon.com Services LLC in Bellevue, WA is hiring a Data Engineer to design data tools and infrastructure that support analysis at scale. This onsite role emphasizes building data pipelines and applying Generative AI to enhance data source discovery, pipeline development, and AI-integrated data platforms.

You will collaborate with stakeholders to address big data warehousing challenges and develop self-service capabilities for BI teams and data scientists, helping identify opportunities and

Qualifications

• 1+ years of data engineering experience.
• Experience with data modeling, warehousing, and building ETL pipelines.
• Experience with SQL-based languages (e.g., SQL, HiveQL, SparkSQL).
• Experience with Python or shell scripting.
• Experience with Hadoop, Hive, Spark, EMR.

Responsibilities

• Design tools and infrastructure to enable analysis of large volumes of data.
• Help address big data warehousing challenges.
• Collaborate with stakeholders to design and implement data solutions aligned to key business questions.
• Use Generative AI to optimize data source discovery and pipeline development.
• Build intelligent agents to help BI Engineers and Scientists identify opportunities.
• Create self-service capabilities for stakeholders.
• Develop AI-integrated data platforms.

Skills

Data engineering

ETL pipelines

SQL

Python

Big data

Tools

Hadoop

Hive

Spark

EMR

Informatica

Job description

Amazon.com Services LLC in Bellevue, WA is hiring a Data Engineer to design data tools and infrastructure that support analysis at scale. This onsite role emphasizes building data pipelines and applying Generative AI to enhance data source discovery, pipeline development, and AI-integrated data platforms.

You will collaborate with stakeholders to address big data warehousing challenges and develop self-service capabilities for BI teams and data scientists, helping identify opportunities and