Data Engineer, Denied Party Screening, AWS Compliance & Security Assurance

Amazon • Seattle, WA

6d

About The Position

Amazon seeks an experienced Data Engineer to join the DPS (Deny 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, 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, build up data pipelines and datasets to meet business needs. You
stay abreast of emerging technologies, investigating and implementing where
appropriate.

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.

Requirements

• 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

Nice To Haves

• 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

Responsibilities

• Design, implement, and support data warehouse/ data lake infrastructure using AWS bigdata 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 model 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 those 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

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed