Data Engineer II

Amazon.com Services LLC

Bellevue (WA)

On-site

USD 132,000 - 179,000

Full time

14 days+

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Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

You will own end-to-end data lineage, model schemas, and deliver features across backend services and tools, while ensuring reliability, observability, and security. The team collaborates with stakeholders to translate domain knowledge into machine-readable

Qualifications

Minimum of 3 years of data engineering experience.
Bachelor’s degree or higher in a related field or equivalent professional experience.
Proficiency with SQL and data warehousing concepts.

Responsibilities

Design, implement, and manage production SQL data pipelines in a cloud data warehouse with reliability and observability.
Model entity schemas, define metrics, and own end-to-end data lineage from raw sources to consumption.
Deliver features across backend services and frontend interfaces for team tools.
Collaborate with stakeholders to translate business context into machine-readable definitions.

Skills

Data engineering

SQL

Python

Java

ETL/ELT

Data modeling

Cloud data warehouse

Education

Bachelor's degree or higher

Tools

Redshift

Oracle

NoSQL

AWS Glue

EMR

Kinesis

Firehose

Lambda

IAM

Job description

Amazon.com Services LLC is seeking a Data Engineer II to design, build, and operate production SQL data pipelines within a cloud data warehouse, enabling AI-driven analytics at enterprise scale. This onsite role is based in Bellevue, WA, with a compensation range of USD 132,100 to 178,800 per year and requires a bachelor’s degree or higher along with at least three years of data engineering experience.

Responsibilities

Design, implement, and manage production SQL data pipelines in a cloud data warehouse with reliability and observability requirements.
Model entity schemas, establish metric definitions, and own end-to-end data lineage from raw sources through transformations to consumption.
Deliver features across backend services and the frontend interfaces for our team’s tools.
Contribute to an expanding semantic layer encoding business context for AI agents to consume.
Collaborate with business stakeholders to translate operational expertise into structured, machine-readable definitions.
Ensure operational health, alerts, on‑call readiness, and access controls for your deployments.
Process large volumes of daily operational data from multiple upstream sources with strong reliability, freshness, and observability.
Extend full‑stack web applications used by business teams, shipping backend and frontend features to make data captureable, reviewable, and actionable at the source.
Enhance the semantic layer with version‑controlled definitions of metrics, entities, relationships, and business context so knowledge resides in code and can be consumed by AI tools.
Collaborate with business stakeholders to translate domain knowledge into structured, machine‑readable definitions and tables.
Own the operational health of deployments, including production alerts, on‑call duties, ticket intake, row‑level security, and pipeline observability.
Seek opportunities to reduce manual analysis by moving toward natural language interfaces, richer entity relationships, and more autonomous investigation.
Explore advances in semantic data modeling, knowledge representation, retrieval, and prompt engineering to improve how AI systems reason over data.
Produce design documents, scope documents, and runbooks to keep work reviewable, maintainable, and durable.

Requirements

A minimum of three years of data engineering experience.
Bachelor's degree or higher in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or related fields, or at least three years of professional software development experience.
Proficiency in one or more object‑oriented languages such as Java, C/C++, or Python.
Experience with data warehouse architectures, data modeling, infrastructure components, ETL/ELT and reporting/analytic tools, data structures, and hands‑on SQL coding.
Experience with Redshift, Oracle, NoSQL, and related technologies.

Technologies