Senior Data Engineer/Architect, WWPS ProServe Data and Machine Learning
Amazon, Seattle, WA, United States
Senior Data Engineer/Architect – WWPS ProServe Data and Machine Learning (AWS Professional Services). This customer‑facing role requires a U.S. citizen with an active Top Secret security clearance. The position is based in the United States (Arlington, VA or Herndon, VA) and is not a remote role. Travel to client sites may be required.
Key job responsibilities
Help clarify customer business outcomes during project discovery and translate them into data architecture and engineering solutions.
Design, build, and optimize secure, scalable, reliable, performant, and cost‑effective data analytics applications.
Collaborate with stakeholders to gather requirements, assess current infrastructure, and propose effective data migration and modernization strategies.
Identify, mitigate, and communicate risks related to solution and service constraints, making informed technical trade‑offs.
Act as a trusted advisor to customers on industry trends, emerging data technologies, and innovative solutions.
Share knowledge within the organization through mentoring, training, and creating reusable artifacts.
Basic Qualifications
Bachelor’s degree in computer science, engineering, mathematics, or equivalent.
5+ years of database experience (SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis).
Experience with SQL, Python, schema definition, and software engineering best practices (secure, testable, maintainable code).
Understanding of distributed systems, data integration techniques (ETL vs. federation), database optimization (partitioning, indexing), and relational database performance tuning.
Active U.S. Government Top Secret or higher security clearance.
Preferred Qualifications
Experience building data platforms with AWS services such as Glue, Lake Formation, Athena, Kinesis, and Lambda.
Experience with CI/CD automation (CDK or Terraform), physical data modeling (Dimensional, Data Vault), and data pipeline optimization.
Experience leading end‑to‑end data engineering projects, including migrating on‑premises data applications to cloud‑native architectures.
Experience interfacing with customers at different organizational levels to translate requirements into scalable data architectures.
Knowledge of security and compliance standards (FedRAMP, NIST, HIPAA).
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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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Key job responsibilities
Help clarify customer business outcomes during project discovery and translate them into data architecture and engineering solutions.
Design, build, and optimize secure, scalable, reliable, performant, and cost‑effective data analytics applications.
Collaborate with stakeholders to gather requirements, assess current infrastructure, and propose effective data migration and modernization strategies.
Identify, mitigate, and communicate risks related to solution and service constraints, making informed technical trade‑offs.
Act as a trusted advisor to customers on industry trends, emerging data technologies, and innovative solutions.
Share knowledge within the organization through mentoring, training, and creating reusable artifacts.
Basic Qualifications
Bachelor’s degree in computer science, engineering, mathematics, or equivalent.
5+ years of database experience (SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis).
Experience with SQL, Python, schema definition, and software engineering best practices (secure, testable, maintainable code).
Understanding of distributed systems, data integration techniques (ETL vs. federation), database optimization (partitioning, indexing), and relational database performance tuning.
Active U.S. Government Top Secret or higher security clearance.
Preferred Qualifications
Experience building data platforms with AWS services such as Glue, Lake Formation, Athena, Kinesis, and Lambda.
Experience with CI/CD automation (CDK or Terraform), physical data modeling (Dimensional, Data Vault), and data pipeline optimization.
Experience leading end‑to‑end data engineering projects, including migrating on‑premises data applications to cloud‑native architectures.
Experience interfacing with customers at different organizational levels to translate requirements into scalable data architectures.
Knowledge of security and compliance standards (FedRAMP, NIST, HIPAA).
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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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