Data Engineer II: Build Context‑Driven Pipelines

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

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC in Seattle is seeking a talented Data Engineer to own context-driven data pipelines across the AWS data platform. You will build source-of-truth datasets, design scalable ETL/ELT workflows, and partner with Software, Product, and Data Engineering teams to empower self-service analytics and AI use cases.

The ideal candidate has 4+ years of data engineering experience, strong data modeling, and proficiency in Python or Java.

Qualifications

• 4 years of data engineering experience.
• Bachelor’s degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS.
• Experience with SQL.

Responsibilities

• Know why you’re building, not just what. Ask sharp questions first, understand your data and its significance, reuse before you rebuild, and set clear data contracts so data is always traceable to its source — and correct.
• Own the design, development, and operation of scalable, production-grade, context-driven data pipelines — including the infrastructure behind them — keeping them lightweight, cost-efficient, auditable, and highly available to power metrics, reporting, analytics, and ML/LLM use cases.
• Build context-rich “source of truth” datasets and reusable, dimensional data models that track the infrastructure delivery lifecycle (intake → deployment → decommission), serving as a trusted, intuitive-to-query foundation for downstream consumers while keeping tech debt in check.
• Design data models and ETL/ELT workflows to ingest, transform, and integrate data from diverse sources using AWS services (e.g., S3, Redshift, Glue, EMR, Athena, Lambda) and internal Amazon data platform tools.
• Define and champion data quality/ engineering and governance best practices — validation, monitoring/alerting, testing, design standards, documentation, and governance — to keep pipelines accurate, trustworthy, and well-maintained.
• Partner with Software, Product, and other Data Engineering teams to source and model the right business entities, so any team can answer their own questions without waiting in a queue.
• Troubleshoot operational and data-quality issues with root-cause analysis and durable fixes; audit existing pipelines, jobs, and queries, and recommend improvements to upstream sources for greater accuracy, simplicity, and scalability

Skills

Data engineering

Data modeling

ETL pipelines

SQL experience

Independent delivery

Education

Bachelor’s degree in CS/Engineering

Tools

Python

Java

Scala

Job description

Amazon.com Services LLC in Seattle is seeking a talented Data Engineer to own context-driven data pipelines across the AWS data platform. You will build source-of-truth datasets, design scalable ETL/ELT workflows, and partner with Software, Product, and Data Engineering teams to empower self-service analytics and AI use cases.

The ideal candidate has 4+ years of data engineering experience, strong data modeling, and proficiency in Python or Java.