Data Engineer, Denied Party Screening, AWS Compliance & Security Assurance
Amazon Web Services (AWS) · Dallas, TX
- On site
- Full-time
- $155,000 / year
- Dallas, TX
Job highlights
- Design and implement scalable AWS data infrastructure.
- Develop and manage ETL pipelines for diverse data sources.
- Build real-time data pipelines using AWS technologies.
- Collaborate on advanced analytics and reporting solutions.
- Mentor engineers and drive team culture.
About the role
Data Engineer, Denied Party Screening, AWS Compliance & Security Assurance
Amazon Web Services (AWS) is seeking an experienced Data Engineer to join the Denied Party Screening (DPS) team. The mission of the DPS team is to prevent denied parties from transacting with Amazon businesses, including AWS, customers, vendors, sellers, and subsidiaries. We screen billions of events daily, integrate with Tier 1 systems, build DPS systems, and address unique scaling challenges.
As a Data Engineer, you will design, implement, and support scalable data infrastructure solutions. This includes integrating with multi-heterogeneous data sources, aggregating and retrieving data rapidly and securely, and curating data for reporting, analysis, machine learning models, and ad-hoc data requests. You will gain exposure to cutting-edge AWS big data technologies. Excellent business and communication skills are essential for collaborating with business owners and tech leaders to gather infrastructure requirements, design data infrastructure, and build data pipelines and datasets to meet business needs. You will stay current with emerging technologies and implement them 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, and Athena.
- Develop and manage ETL processes to source data from various financial, AWS networking, and operational systems to create a unified data model for analytics and reporting.
- Create and support 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 for financial model development, statistical analysis, and prediction using rich datasets.
- Conduct continuous research on the latest big data and visualization technologies to introduce new capabilities and enhance efficiency.
- Utilize business intelligence and visualization software (e.g., QuickSight) to develop dashboards for senior leadership.
- Empower technical and non-technical internal customers to drive their own analytics and reporting (self-serve reporting) and provide support for ad-hoc reporting.
- Work closely with team members to drive real-time model implementations for monitoring and alerting of risk systems.
- Manage numerous concurrent requests strategically, prioritizing as needed.
- Partner and collaborate across teams and roles to deliver results.
- Mentor other engineers, positively influence team culture, and contribute to team growth.
About The Team
Denied Party Screening (DPS) is part of Amazon Security, an organization dedicated to driving bar-raising security engagements. The vision of the Amazon DPS program is to ensure that over 1 billion Amazon accounts across consumers, sellers, developers, employees, and all other Amazon parties are not denied parties, 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 paramount to maintaining customer trust and delivering exceptional customer experiences. Our organization is responsible for establishing and upholding a high standard of security across all of Amazon’s products and services.
Work/Life Balance
We are committed to work-life harmony. Achieving success at work should not require sacrifices at home, which is why flexible work hours and arrangements are integral to our culture. When we feel supported both in the workplace and at home, there are no limits to what we can achieve.
Inclusive Team Culture
In Amazon Security, curiosity and continuous learning are inherent. Ongoing DEI events and learning experiences encourage us to keep learning and embrace our uniqueness. Addressing the most challenging security issues requires us to seek out and celebrate diverse ideas, perspectives, and voices.
Training and Career Growth
We are constantly raising our performance bar as we aspire to be Earth's Best Employer. You will find abundant opportunities for knowledge sharing, training, and other career-advancing resources to support your development into a well-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, or 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 concerning 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 on data engineering best practices.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or any 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, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, TX, Dallas - 132,100.00 - 178,800.00 USD annually
USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually
Company - Amazon.com Services LLC
Job ID: A3160403
Key skills/competency
- Data Engineering
- AWS
- Python
- ETL
- Data Warehousing
- Data Lake
- Big Data
- Spark
- Redshift
- SQL
Skills & topics
- Data Engineer
- AWS
- Python
- ETL
- Data Warehousing
- Data Lake
- Big Data
- Spark
- Redshift
- Compliance
- Security Assurance
- EMR
- Glue
- Athena
- QuickSight
- Cloud Computing
- Database
- Software Engineering
How to get hired
- Tailor your resume: Highlight AWS data engineering, big data technologies (Spark, EMR), and Python proficiency. Quantify achievements in past roles.
- Showcase AWS expertise: Emphasize experience with Redshift, S3, Glue, EMR, Kinesis, and IAM in your application.
- Demonstrate project ownership: Detail end-to-end projects you've independently delivered, showcasing your ability to manage complexity.
- Prepare for technical interviews: Be ready to discuss data modeling, ETL design, distributed systems, and problem-solving with AWS services.
- Research Amazon's culture: Understand their customer obsession, leadership principles, and commitment to security and innovation.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the primary AWS technologies used by the Data Engineer on the DPS team at Amazon Web Services?
- The Data Engineer on the Denied Party Screening team at Amazon Web Services will primarily work with AWS big data technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions. Experience with data warehousing and data lake concepts on AWS is crucial.
- What level of experience is required for the Data Engineer role at AWS?
- This Data Engineer role at AWS requires a minimum of 5 years of data engineering experience. Preferred qualifications include experience with various AWS services, non-relational databases, distributed systems, and technical leadership.
- What programming languages are essential for the Data Engineer position at Amazon?
- Proficiency in at least one modern programming language like Python is essential for this Data Engineer role at Amazon. Experience with languages such as C++, C#, Java, Golang, PowerShell, Ruby, Scala, or NodeJS is also beneficial.
- How does Amazon Web Services approach work-life balance for its Data Engineers?
- Amazon Web Services values work-life harmony, recognizing that success at work should not come at the expense of personal life. This Data Engineer role benefits from flexible work hours and arrangements as part of the company's supportive culture.
- What is the core mission of the Denied Party Screening (DPS) team at AWS?
- The core mission of the Denied Party Screening (DPS) team at AWS is to prevent denied parties from transacting with any Amazon business. This involves screening billions of events daily to ensure compliance and security across Amazon's vast network of customers, vendors, and subsidiaries.
- Can I expect to work with real-time data processing in this Data Engineer role at AWS?
- Yes, this Data Engineer role at AWS involves the creation and support of real-time data pipelines built on AWS technologies like EMR, Glue, Redshift/Spectrum, and Athena, as well as working closely with team members to drive real-time model implementations for monitoring and alerting.
- What opportunities for career growth are available for a Data Engineer at Amazon?
- Amazon offers extensive training and career advancement resources to help Data Engineers develop into well-rounded professionals. You'll find abundant knowledge-sharing opportunities and continuous learning to help you raise your performance bar and grow within the company.