In this role, you'll champion a forward-thinking approach to data infrastructure that anticipates the evolving needs of AI systems while maintaining the reliability and performance that business operations demand. You'll help shape our technical roadmap for data systems that will serve as the foundation for our organization's AI transformation journey.
Key job responsibilities
5+ years of data engineering, building and operating production pipelines and warehouses.
Experience building data infrastructure that serves AI systems and autonomous agents, not just human analysts, including machine-consumable interfaces, metadata, and documentation.
Experience with GenAI data patterns end to end: chunking, embeddings, and vector stores for retrieval-augmented generation.
Experience building and maintaining datasets and feature pipelines for ML/GenAI training, fine-tuning, and inference (Amazon SageMaker, Bedrock, or equivalent).
Experience implementing data quality, lineage, and observability that AI workloads depend on including validation, freshness/anomaly monitoring, and alerting at scale.
5+ years of Python (or Scala/Java) and advanced SQL, including performance tuning at scale.
Experience with batch and streaming ETL/ELT on AWS (Glue, EMR/Spark, S3, Athena) and a production cloud data warehouse (Amazon Redshift or equivalent).
Experience designing data models and schemas for analytical, operational, and AI/retrieval workloads.
Experience with workflow orchestration (Step Functions, Airflow, or Glue Workflows).
7+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
Experience with SQL
Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
Experience mentoring team members on best practices
Experience with MPP databases such as Amazon Redshift
Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
Experience building data infrastructure that serves AI systems and autonomous agents, not just human analysts, including machine-consumable interfaces, metadata, and documentation.
Experience with GenAI data patterns end to end: chunking, embeddings, and vector stores for retrieval-augmented generation.
Experience building and maintaining datasets and feature pipelines for ML/GenAI training, fine-tuning, and inference (Amazon SageMaker, Bedrock, or equivalent).
Experience implementing data quality, lineage, and observability that AI workloads depend on including validation, freshness/anomaly monitoring, and alerting at scale.
Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
Experience operating large data warehouses
Experience providing technical leadership and mentoring other engineers for best practices on data engineering
Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Knowledge of distributed systems as it pertains to data storage and computing
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t 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 https://amazon.jobs/en/benefits.
USA, WA, Seattle - 154,600.00 - 209,100.00 USD annually
