Data Engineer I, Data : Science Engineering, AWS ...

DescriptionWithin 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 u2014 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 u2014 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, hasnu2019t followed a traditional path, or includes alternative experiences, donu2019t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the worldu2019s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating u2014 thatu2019s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 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, thereu2019s nothing we canu2019t achieve in the cloud. Inclusive Team Culture Here at AWS, itu2019s 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 Weu2019re continuously raising our performance bar as we strive to become Earthu2019s Best Employer. Thatu2019s why youu2019ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Basic Qualifications- 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 disciplinePreferred Qualifications- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or 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 for more information. If the country/region youu2019re applying in isnu2019t 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 . USA, WA, Seattle - 101,300.00 - 160,000.00 USD annually

Created: 2026-04-04