Data Engineer, Denied Party Screening

Data Engineer, Denied Party Screening

Amazon seeks an experienced Data Engineer to join the DPS (Denied Party Screening) team. Our mission is to prevent denied parties from transacting with Amazon businesses, including AWS, customers, vendors, sellers, subsidiaries, etc. We screen billions of events every day. We integrate with Tier 1 systems, build DPS systems, and deal with unique scaling challenges.

As a Data Engineer, you will design, implement, and support scalable data infrastructure solutions to integrate with multi-heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, and curate data that can be used in reporting, analysis, machine learning models, and ad-hoc data requests. You will be exposed to cutting-edge AWS big data technologies. You should have excellent business and communication skills to be able to work with business owners and Tech leaders to gather infrastructure requirements, design data infrastructure, and build up data pipelines and datasets to meet business needs. You stay abreast of emerging technologies, investigating and implementing where appropriate.

Key Job Responsibilities

• Design, implement, and support data warehouse/data lake infrastructure using AWS big data stack, Python, Redshift, QuickSight, Glue/Lake Formation, EMR/Spark, Athena etc.
• Develop and manage ETLs to source data from various financial, AWS networking, and operational systems and create unified data models for analytics and reporting.
• Creation and support of real-time data pipelines built on AWS technologies including EMR, Glue, Redshift/Spectrum, and Athena.
• Collaborate with other Engineering teams, Product/Finance Managers/Analysts to implement advanced analytics algorithms that exploit our rich datasets for financial model development, statistical analysis, prediction, etc.
• Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency.
• Use business intelligence and visualization software (e.g., QuickSight) to develop dashboards that are used by senior leadership.
• Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
• Working closely with team members to drive real-time model implementations for monitoring and alerting of risk systems.
• Manage numerous requests concurrently and strategically, prioritizing when necessary.
• Partner/collaborate across teams/roles to deliver results.
• Mentor other engineers, influence positively team culture, and help grow the team.

About The Team

Denied Party Screening (DPS) is a part of Amazon Security, an organization designed to drive bar-raising security engagements. The vision of the Amazon DPS program is to ensure that 1+ billion Amazon accounts spanning across consumers, sellers, developers, employees, and all other Amazon party, are not a denied party, located or incorporated in a sanctioned region or country, or owned or controlled by or subject to the jurisdiction of the government of a sanctioned country.

Why Amazon Security

At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Inclusive Team Culture

In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.

Training and Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.

Basic Qualifications

• 5+ years of data engineering experience.
• Experience programming with at least one modern language such as C++, C#, Java, Python, Golang, PowerShell, Ruby.
• Experience working on and delivering end-to-end projects independently.
• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR.

Preferred Qualifications

• 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).
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS.
• Experience with distributed systems as it pertains to data storage and computing.
• Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets.
• Experience providing technical leadership and mentoring other engineers for best practices on data engineering.

Key Skills/Competency

• Data Engineering
• AWS Big Data
• ETL Development
• Real-time Data Pipelines
• Python Programming
• Data Warehousing
• Data Lake
• SQL
• Machine Learning Data
• Compliance Data