Senior Data Engineer

Senior Data Engineer role at Amazon Development Center U.S., Inc. in Seattle, WA onsite, owning 3-5 data domains end-to-end, operating hundreds of pipelines, and guiding architectural decisions with AWS leadership impact.

Responsibilities

• Assess data processing tools for limitations and opportunities, lead improvements, establish guidelines, and enforce best practices across pipelines. Example: redesigning ingestion frameworks to accommodate new AWS service telemetry data or creating reusable transformation patterns used by multiple teams.
• Define and own team-level data architecture to align with business problems and data challenges, ensuring security, scalability, and cost efficiency; balance short-term technology needs with long-term business goals.
• Deliver high-quality, maintainable code that is secure, scalable, and extensible, with solutions easy for others to contribute to and reuse; focus on simplifying and removing bottlenecks.
• Define and own team-level infrastructure architecture; anticipate data management and access patterns, evolve the technology stack to remove bottlenecks, and deliver secure, durable systems with clear guidelines for automation.
• Solve complex ambiguous problems, such as cross-domain data models unifying billing, usage, and service telemetry, or merging datasets to enable previously unsolvable analyses; identify potential data contract gaps.
• Break work into parallel tasks that teams can execute independently and reassemble successfully; drive projects to completion with interdependencies across peers or teams.
• Influence related teams' data architecture and software design; provide technical assessments for promotions; actively mentor others and build consensus in the face of discordant views.
• Champion data engineering best practices, including Data Discovery, Naming Conventions, Operational Excellence, and Data Security; ensure data is auditable, available, and accessible.
• Proactively address data architecture deficiencies and propose cross-team initiatives; advance improvements through code reviews, design discussions, planning, and operational reviews.
• Participate in on-call rotation and own the operational health of data systems; establish monitoring, alarming, runbooks, and SLA tracking; pursue ongoing reliability enhancements.

Requirements

• 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 and operating highly available, distributed systems for data extraction, ingestion, and processing of large data sets

Technologies

• AWS EMR
• AWS Glue
• Amazon Redshift
• AWS Lambda
• Large Language Models (LLMs)
• Hadoop
• Hive
• Spark
• Python
• Java
• Scala
• NodeJS
• SQL

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription)
• Basic Life & AD&D insurance and option for Supplemental life plans
• Employee Assistance Program (EAP)
• Mental Health Support
• Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave

Details

• Location: Seattle, WA onsite
• Salary: USD 154,600 - 209,100 per year
• On-site work: Yes
• Minimum experience: 7 years