DataEngineer

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 perm