Data Engineer I: Build Scalable Pipelines & Insights

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

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon.com Services LLC in Bellevue, WA is seeking a Data Engineer to design, build, and maintain scalable data pipelines and ETL processes. You will collaborate with finance and BI teams to deliver robust data architectures and reliable reporting.

You will work with Python, Spark, SQL, and AWS services to integrate diverse data sources, ensure data quality, and support analytics, ML models, and ad-hoc requests. Strong communication with business stakeholders is essential.

Qualifications

• 1 year of data engineering experience.
• Experience with data modeling, warehousing and ETL pipelines.
• Experience with one or more query languages (e.g., SQL, HiveQL, SparkSQL).
• Experience with one or more scripting languages (e.g., Python, shell).
• Experience with AI-assisted development tools in day-to-day engineering work.

Responsibilities

• Design, build, and maintain complex data solutions and ETL pipelines using Python, Spark, SQL, and AWS services.
• Architect scalable data pipelines powering reporting and analytics for internal Finance customers.
• Integrate data across heterogeneous sources with focus on data quality and sound design trade-offs.
• Partner with finance managers, developers, and BI engineers to deliver data architecture projects.
• Drive engineering excellence through code reviews, design discussions, and planning; improve reporting processes and self-service automation.
• Identify and implement process improvements to scale solutions and support new reporting dimensions.

Skills

Data engineering

Data modeling

ETL pipelines

SQL

Python

Scripting

AI-assisted tools

Tools

Hadoop

Hive

Spark

EMR

Informatica

ODI

SSIS

Datastage

Job description

Amazon.com Services LLC in Bellevue, WA is seeking a Data Engineer to design, build, and maintain scalable data pipelines and ETL processes. You will collaborate with finance and BI teams to deliver robust data architectures and reliable reporting.

You will work with Python, Spark, SQL, and AWS services to integrate diverse data sources, ensure data quality, and support analytics, ML models, and ad-hoc requests. Strong communication with business stakeholders is essential.