Data Engineer I, Data : Science Engineering, AWS Marketing

Amazon • Seattle, WA

7d

About The Position

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.

Requirements

• 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

Nice To Haves

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

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.

Benefits

• 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 https://amazon.jobs/en/benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level