Data Engineer, AWS Analytics Engineering

- 5+ years of data engineering experience
- 3+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 3+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- 3+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience programming with at least one modern language such as Python, Ruby, Golang, Java, C++, C#, Rust
- Experience with enterprise-scale infrastructure or development-based cloud programs/projects in a related industry
- Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience implementing data governance controls: access management, encryption, data classification, and audit logging
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience with AWS services including S3, Redshift, EMR and RDS
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience building data products incrementally and integrating and managing data sets from multiple sources
- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
- Experience building compliance and audit frameworks: automated data lineage tracking, retention policy enforcement, and regulatory audit support

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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 - 132,100.00 - 178,800.00 USD annually
The AWS Analytics Engineering (AAE) organization is the analytics backbone of AWS — we build and operate the data platform that powers business decisions across more than 150 AWS services. Every insight surfaced to AWS product leadership, from service adoption trends to revenue drivers, flows through systems our team designs, builds, and maintains.

We operate at massive scale — processing petabytes of data daily through thousands of jobs consisting of transformations, reporting queries, ingestions, and infrastructure management scripts. As AWS launches new services and features at an accelerating pace, the need for a unified, self-service Data Ingestion Platform has become critical.

We are seeking a Data Engineer to join our Data Ingestion Platform team. In this role, you will design, build, and operate the next-generation ingestion service that automatically onboards data from any new AWS service or feature at launch — without manual intervention. You will build scalable ingestion frameworks capable of handling petabytes of data, implement big data procurement pipelines, and establish the governance, compliance, and audit controls that ensure every data flowing through the platform meets AWS’s security and data integrity standards.

The platform you build must scale to N services — meaning that as AWS’s service portfolio grows, your ingestion infrastructure grows with it. You will work on event-driven architectures, self-registration mechanisms, and configuration-driven onboarding so that new data sources are ingested automatically, reliably, and with full lineage and audit trails.

The ideal candidate is a strong engineer who is passionate about building platforms, thinks in terms of frameworks and abstractions rather than one-off pipelines, and is excited about building the foundational layer that enables all of AAE’s analytics capabilities.