Senior Distributed Data Systems Engineer

Amazon

Seattle (WA)

On-site

USD 168,100 - 227,400

Full time

14 days+

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Benefits offered by this job

RSUs
Health insurance
401(k) matching
Paid time off
Parental leave

Job summary

Amazon is seeking a Senior Software Development Engineer to build and optimize distributed systems that process cost and usage data at massive scale for AWS services. You will work on batch and streaming pipelines using Spark and EMR, tackling data freshness, performance, and cost-efficiency while delivering insights to customers within minutes.

You will collaborate with product, science, and partner teams to ensure accurate, timely data delivery and drive architectural standards across the

Qualifications

  • 5+ years of non-internship professional software development experience.
  • 5+ years of programming with at least one software programming language experience.
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
  • Experience as a mentor, tech lead or leading an engineering team.

Responsibilities

  • Design and implement large-scale distributed data processing systems handling trillions of records
  • Build and optimize batch and streaming pipelines for throughput, latency, and cost efficiency
  • Drive technical decisions on architecture, data modeling, and system design
  • Mentor engineers, lead design reviews, and contribute to team-wide engineering standards
  • Own operational excellence for your systems — including monitoring, alarming, runbooks, and on-call
  • Collaborate with product, science, and partner teams to deliver customer-facing features

Skills

Software development
Mentor / tech lead
Architecture design leadership

Education

Bachelor's degree in Computer Science

Job description

Amazon is seeking a Senior Software Development Engineer to build and optimize distributed systems that process cost and usage data at massive scale for AWS services. You will work on batch and streaming pipelines using Spark and EMR, tackling data freshness, performance, and cost-efficiency while delivering insights to customers within minutes.

You will collaborate with product, science, and partner teams to ensure accurate, timely data delivery and drive architectural standards across the

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