Aws Data Engineer Jobs in Washington

Within AWS Marketing the Data Science Engineering (D:SE) team builds and operates the marketing data platform that fuels attribution models, ROI measurement, customer journey analytics, and campaign optimization, enabling multi-billion dollar marketing investment decisions. Team powers AWS Marketing with a world-class marketing data model and science solutions as a service, leveraging GenAI.

We're looking for a Data Engineer to help us build and scale our next-generation marketing data infrastructure (Jarvis 2.0) and GenAI initiatives. You'll work with a serverless, AWS-native stack i.e. Redshift, S3, Glue, Lambda, SageMaker, Step Functions, SNS, CloudWatch, and more — to deliver the unified marketing data model that serves new GenAI initiatives, measurement scientists, marketing analysts, and downstream APIs across AWS Marketing.

You'll join a tight, high-impact team of data engineers, ML engineers, and applied scientists solving problems at the intersection of marketing analytics, data science enablement, and platform engineering. You'll experience a culture that values ownership, cross-functional collaboration, and data-driven decision making.

Key job responsibilities

• Develop and maintain automated ETL/ELT pipelines (with monitoring and alerting) using Python, Spark, SQL, and AWS services (S3, Glue, Lambda, Step Functions, SNS, SQS, CloudWatch).
• Build and optimize the Gold data sets in marketing data model — designing fact and dimension tables that unify customer journey, web analytics, campaign, revenue, and attribution data at enterprise scale.
• Develop and optimize Redshift and data lake tables using best practices for DDL, physical/logical modeling, data partitioning, compression, and query performance tuning.
• Build and maintain data quality frameworks, validation, reconciliation, anomaly detection to ensure trusted, reliable data for downstream science and analytics consumers.
• Develop and maintain data security, access controls, encryption, and permissions for enterprise-scale data warehouse and data lake implementations.
• Maintain data catalogs, metadata, lineage documentation, and self-service tooling for internal marketing and science consumers.
• Partner with measurement scientists, marketing analysts, and cross-functional engineering teams to gather requirements and deliver data solutions that directly inform marketing investment strategy.

- Contribute to API-first data delivery patterns, enabling science-as-a-service consumption of marketing data assets.

About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?

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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 in the cloud.
Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
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