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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer, Data : Science Engineering, AWS Marketing - **Company:** Amazon.com, Inc. - **Location:** Seattle, WA, United States - **Salary:** $101,300.0 - $160,000.0 - **Contract:** Permanent contract - **Skills:** Query Performance, Application Programming Interfaces (APIs), Amazon Web Services, Amazon S3, Big Data, Information Systems, Computer Engineering, Data Definition Language, Information Engineering, Extract Transform Load (ETL), Data Systems, Data Warehousing, Query Languages, IBM InfoSphere DataStage, Decision Support Systems, Apache Hadoop, Apache Hive, Information Management, Python (Programming Language), MultiDimensional EXpressions, Scala (Programming Language), Amazon Simple Notification Service (SNS), PL-SQL, SQL Databases, SQL Server Integration Services, Web Analytics, Apache Spark, Electronic Medical Records, Data Lakes, Information Technology, Data Delivery, Api Design, Cloudwatch, Amazon Simple Queue Service (SQS), Data Pipelines, Serverless Computing - **Published:** September 17, 2026 - **Apply:** https://dejobs.org/x/x/C55AC905AD764141B0B73B1E4440EBEA/job/ ## About the Role * 1+ years of data engineering experience * Experience with data modeling, warehousing and building ETL pipelines * Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) * Bachelor's degree in Computer Science, Computer Engineering, Information Management, Information Systems, or other related discipline Preferred Qualifications * Experience with big data technologies such as: Hadoop, Hive, Spark, EMR * Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. ## Description 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., * 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Hate organising your photos? 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