Are you interested in playing a pivotal role in building innovative technology that protects Amazon’s award-winning Customer Experience?
Threat Detection Technologies team, in Customer Engagement Technologies (CET) group, is responsible for automating detection, and neutralization, of cyber-
security threats in Amazon's global contact center network. Among other things, we build monitoring systems that collect data at scale, and use machine learning (ML) to detect threatening behaviors.
We are looking for a Senior Data Engineer to play a key role in our threat research program, with emphasis on detecting anomalies in large unstructured data sets.
Successful candidate will work in lock-step with ML scientists, threat analysts, security investigators, program managers, and other stakeholders across the organization in gathering, reducing, enriching, and analyzing data for threatening user behaviors in CET systems.
Collaborate with ML Scientists and threat analysts to implement advanced analytics queries for statistical analysis, and machine learning.
Build robust and scalable data integration (ETL) pipelines using SQL, EMR, Python and Spark.
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
Translate data into actionable insights for stakeholders.
Load and maintain data feeds of security log and audit information into Splunk, and Elastic Search security investigation tools.
Build data visualization dashboards in tools like Tableau, QuickSight, and Splunk.
Manage and prioritize a project backlog.
Amazon is an Equal Opportunity-Affirmative Action Employer Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
Bachelor's degree or higher in a quantitative / technical field (i.e. Computer Science, Statistics, Engineering).
7+ years of relevant experience in one of the following areas : Data engineering, business intelligence or business analytics.
5+ years of hands-on experience in writing complex, highly-optimized SQL queries across large data sets.
2+ years of experience in scripting languages like Python etc.
Demonstrated strength in data modeling, ETL development, and data warehousing.
Experience with data visualization tools (i.e. Tableau, QuickSight)
Experience with AWS services including S3, Redshift, EMR, Kinesis.
Experience with Big Data Technologies (i.e. Hadoop, Hive, Spark, etc.).
Experience in working and delivering end-to-end projects independently.
Demonstrated experience managing and prioritizing a project backlog.
Familiarity with Eider and Data Craft
Familiarity with statistical models and data mining algorithms
Familiarity with Data Science techniques such as clustering, anomaly detection leveraging data analysis tools (i.e. : Splunk, Behavioral Analytics, SQL, R, etc.).
Experience with Splunk.
Demonstrated experience defining and driving an analytics roadmap.