Amazon Web Services (AWS)

Data Engineer II, AWS Analytics Engineering

Seattle, Washington, USA · Mid

Sponsorship not specified$132k-$179kDetected 12 hours ago

Data StructuresCode ReviewSQLRedshiftAWSData EngineeringProcurementOnboardingEHR/EMRLeadership

About the role

We operate at massive scale - processing petabytes of data daily through thousands of jobs consisting of transformations, reporting queries, ingestions, and infrastructure management scripts.
You will work on event-driven architectures, self-registration mechanisms, and configuration-driven onboarding so that new data sources are ingested automatically, reliably, and with full lineage and audit trails.
Identify and resolve data quality issues proactively.

The AWS Analytics Engineering (AAE) organization is the analytics backbone of AWS - we build and operate the data platform that powers business decisions across more than 150 AWS services.
Every insight surfaced to AWS product leadership, from service adoption trends to revenue drivers, flows through systems our team designs, builds, and maintains.
In this role, you will design, build, and operate the next-generation ingestion service that automatically onboards data from any new AWS service or feature at launch - without manual intervention.
The platform you build must scale to N services - as AWS's service portfolio grows, your ingestion infrastructure grows with it.
Implement event-driven architectures and self-registration mechanisms that enable service teams to onboard data sources through standardized, self-service interfaces.
Build and operate big data procurement pipelines at petabyte scale - ensuring reliability, fault-tolerance, cost-effectiveness, and performance across thousands of concurrent ingestion jobs.
Implement automated guardrails, data certification standards, and SLAs for ingestion completeness, freshness, and accuracy.
Make sound architectural trade-offs balancing pragmatic short-term delivery with sustainable long-term design.
Efficiently manage compute, storage, and AWS infrastructure resources - building solutions that are stable, performant, and cost-optimized.
Drive automation to reduce operational toil.

5+ years of data engineering experience.
3+ years of SQL experience.
Experience with data modeling, warehousing and building ETL pipelines.
Experience implementing data governance controls: access management, encryption, data classification, and audit logging
Experience with data modeling, warehousing and building

Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases).

Own operational health for ingestion systems - monitoring, alarming, runbooks, on-call rotation, and incident resolution.

equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

This listing is sourced directly from Amazon Web Services (AWS)'s careers page and normalized into a canonical job model.