Data Engineer II, AWS Analytics Engineering - FDT

About the Position

Data Engineer II, AWS Analytics Engineering - FDT

Senior

105,000 - 130,000 USD/yr

Seattle, WA

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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.

We are seeking a Data Engineer to join our team. This individual will be a significant and autonomous contributor, owning a major portion of the team's data architecture - solving difficult problems, building logical data models, and delivering data pipelines that are stable, performant, and consistently high quality. You will work with engineers and stakeholders across AWS to design data contracts, build ingestion flows, and deliver analytical models that increase self-service access to datasets and business effectiveness.

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Responsibilities

• Identify and resolve data quality issues in processing tools, contribute to improvements and innovation, and ensure best practices in pipelines you design and maintain.
• Build and optimize logical data models and data pipelines for difficult datasets - ensuring solutions are testable, maintainable, and efficient while addressing security, scalability, and cost considerations.
• Make appropriate technical trade-offs at the dataset level, balancing pragmatic short-term decisions with sustainable long-term approaches.
• Produce high-quality code - solutions that are pragmatic, secure, maintainable, and flexible without over-engineering.
• Contribute to infrastructure decisions within the team's data architecture. Efficiently manage resources (system hardware, data storage, query optimization, AWS infrastructure) and build solutions that are stable and performant.
• Solve difficult problems - for example, designing data models that integrate multiple sources within the team's domain, or combining datasets to unlock new analytical capabilities.
• Break down project work into manageable tasks, deliver independently, and collaborate effectively with peers on shared dependencies. Resolve discordant views and build consensus among team members.
• Mentor peers, participate in hiring, and contribute to team knowledge-sharing.
• Drive data engineering best practices within the team - code quality, data certification, dependency management, and operational excellence.
• Drive improvements through code reviews, design discussions, team planning, and operational reviews.
• Participate in on-call rotation and take ownership of operational health for data systems you own - contribute to monitoring, alarming, runbooks, and incident resolution.

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Requirements

• 5+ years of data engineering experience
• 3+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes
• 3+ years of developing and operating large-scale data structures for business intelligence analytics using SQL
• 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL, etc.
• 3+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies and Data Modeling
• Experience communicating with users, other technical teams, and management to collect requirements, describe data modeling decisions, and data engineering strategy

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Nice to Have

• 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 big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
• 4+ years of data warehouse technical architectures, data modeling, infrastructure components, ETL/ELT, and reporting/analytic tools and environments, data structures, and hands-on SQL coding experience
• Experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets, or experience with software development lifecycle

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We Offer

• Competitive salary range: 105,000 - 130,000 USD/year
• Comprehensive benefits including health insurance, 401(k) matching, paid time off, and parental leave
• Opportunity to work in a cutting-edge environment with a leading cloud platform
• Flexible work culture that values work-life balance

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About the Company

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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 Amazon's Accommodations Page for more information.