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

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Data Engineer II, IAM and Abuse Prevention

Amazon

Seattle, Washington, United States

Seattle, Washington, United States

Über

Data Engineer – Identity Security & Abuse Prevention (ISAP) Amazon’s Identity Security & Abuse Prevention (ISAP) team is seeking a Data Engineer to 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. This high‑impact role protects Amazon customers and sellers, modernizing existing pipelines and building greenfield data systems for new security products.
Key Job Responsibilities
Design, implement, and maintain scalable ETL/ELT pipelines for security telemetry, authorization logs, compliance data, and operational metrics from diverse Amazon sources.
Build and optimize data models that enable security engineers and scientists to efficiently query and analyze billions of abuse events.
Create ML‑ready datasets for data science and applied science teams.
Own monitoring, alerting, and observability for all data pipelines, 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‑agent‑centric solutions, ensuring proper data engineering underpins model training and inference.
Leverage GenAI and ML tools to enhance 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.
A Day in the Life You might begin by reviewing pipeline health dashboards, triaging a data freshness alert, and pushing a fix before downstream consumers are impacted. Mid‑morning you attend a design review with the applied science team on a new abuse detection model, collaborating on data schema and feature engineering. After lunch you prototype a new ingestion path for a high‑value customer signal dataset, and later pair with a security engineer to optimize a query powering a leadership dashboard. You finish the day by documenting a proposed architecture for a new data product that correlates device metadata with authentication anomalies, preparing it for team review.
About the Team The ISAP SafeGuard team mixes long‑term, high‑impact projects with near‑term innovative solutions to prevent abuse across Amazon. We balance Bias for Action, Dive Deep, Invent and Simplify, and Customer Trust daily, embracing new approaches, technology, and innovation while ensuring scalable, accurate, and actionable solutions.
Basic Qualifications
3+ years of data engineering experience.
1+ years of developing and operating large‑scale data structures for business intelligence analytics using ETL/ELT processes.
1+ years of developing and operating large‑scale data structures for business intelligence analytics using OLAP technologies.
1+ years of developing and operating large‑scale data structures for business intelligence analytics using data modeling.
1+ years 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 or 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 with strict confidentiality standards.
Experience with large‑scale distributed systems such as Hadoop or Spark.
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.
Salary: 132,100.00 – 178,800.00 USD annually (Seattle, WA, USA). The base salary range is listed below. Your package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance, 401(k) matching, paid time off, and parental leave.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.
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Seattle, Washington, United States

Sprachkenntnisse

English

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