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Data Engineer II, IAM and Abuse PreventionAmazon • Seattle, Washington, United States
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Data Engineer II, IAM and Abuse Prevention

Amazon
  • US
    Seattle, Washington, United States
  • US
    Seattle, Washington, United States
Jetzt Bewerben

Über

Data Engineer II, IAM and Abuse Prevention Amazon’s Identity Security & Abuse Prevention (ISAP) team is seeking a Data Engineer to join our team. We discover, analyze, and quantify security risks across Amazon’s identity and authentication landscape, transforming complex behavioral patterns into actionable intelligence that empowers teams to proactively defend against abuse and unauthorized access.
In this role, you will design, build, and own scalable data pipelines and infrastructure that power security investigations, abuse detection, and intelligence products across multiple Amazon verticals. You will work with large, sensitive datasets spanning security telemetry, authorization logs, customer signals, and device metadata to create the data foundation that enables our security engineers, data scientists, and applied scientists to identify and prevent abuse at scale.
Key Job Responsibilities
Design, implement, and maintain scalable ETL/ELT pipelines that ingest and transform security telemetry, authorization logs, compliance data, and operational metrics from diverse sources across Amazon.
Build and optimize data models that enable security engineers and scientists to efficiently query and analyze abuse patterns across billions of events.
Create ML‑ready datasets for data science and applied science teams.
Own monitoring, alerting, and observability for all data pipelines and data solutions, proactively identifying and resolving data quality issues.
Review and modernize existing data infrastructure, proposing architectural improvements that increase reliability, reduce cost, and improve performance.
Design and build new data capabilities from the ground up to support product launches and investigation team needs.
Partner with security engineers, scientists, and investigators to understand their data requirements and build solutions that accelerate abuse detection and response.
Collaborate with data scientists and applied scientists to support AI and AI‑agent-centric solutions, ensuring proper data engineering underpins model training and inference.
Leverage GenAI and ML tools to enhance your own workflows, automate pipeline operations, and improve data quality processes.
Develop a deep understanding of partner teams and their capabilities, identifying opportunities to consume new signals and vend intelligence data to downstream consumers.
Basic Qualifications
3+ years of data engineering experience.
1+ year of developing and operating large‑scale data structures for business intelligence analytics using ETL/ELT processes.
1+ year of developing and operating large‑scale data structures for business intelligence analytics using OLAP technologies.
1+ year of developing and operating large‑scale data structures for business intelligence analytics using data modeling.
1+ year of developing and operating large‑scale data structures for business intelligence analytics using SQL.
Experience with data modeling, warehousing, and building ETL pipelines.
Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
Preferred Qualifications
Experience with non‑relational databases/data stores (object storage, document or key‑value stores, graph databases, column‑family databases).
Experience building analytic or scientific data products or solutions.
Experience managing confidential and sensitive employee information and adhering to strict confidentiality standards.
Experience with large‑scale distributed systems such as Hadoop, Spark, etc.
Experience using managed ML/AI solutions.
Experience with GenAI tools and techniques for data engineering automation.
Experience with monitoring and alerting frameworks for data pipeline reliability.
Day in the Life You might start your morning reviewing pipeline health dashboards, triaging an alert on a data freshness SLA, and pushing a fix before downstream consumers are impacted. Mid‑morning, you join a design review with the applied science team on a new abuse detection model, working through the data schema and feature engineering requirements together. After lunch, you prototype a new ingestion path for a customer signal dataset that an investigator identified as high‑value for a current case. Later, you pair with a security engineer to optimize a query that powers a leadership dashboard. You close the day by documenting a proposed architecture for a new data product that will correlate device metadata with authentication anomalies, preparing it for team review.
Location: USA, WA, Seattle – Salary range: 132,100.00 – 178,800.00 USD annually.
Salary includes sign‑on payments, restricted stock units (RSUs), and comprehensive benefits such as health insurance, 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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  • Seattle, Washington, United States

Sprachkenntnisse

  • English
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