Jobs · Engineering

Sr. Staff Software Engineer, Big Data Platform

Ladders · United States · 1 mo ago
RemoteRemoteEngineering$160k–$190k/yrFull-time

About the role

For our client, we are seeking a Sr. Staff Software Engineer, Big Data Platform to join the team of a leader in the Consumer Technology space. This role will shape the strategy and technical direction for data infrastructure that powers large-scale data and AI use cases. The ideal candidate will partner closely with cross-functional stakeholders to design systems that deliver reliable, fast, and efficient processing and storage for massive datasets. This is a highly visible opportunity to influence the long-term technical vision for a platform operating at significant scale.

Responsibilities

  • Lead the strategy and technical direction for data infrastructure supporting big data and AI
  • Build and scale frameworks to process petabyte-scale datasets efficiently
  • Collaborate with internal stakeholders on critical business use cases requiring big data
  • Advise the company on reliable, rapid data processing and storage methods at scale
  • Contribute to the team's long-term technical vision and roadmap

Qualifications

  • 10+ years of industry experience in software engineering with a focus on technical excellence
  • 5+ years of experience building and supporting large-scale Kubernetes or big data platforms
  • Deep knowledge of big data and ML technologies like Flink, Spark, and Kubernetes
  • Proficient in programming languages such as Java, Go, Scala, or Python
  • Experience with cloud technologies, particularly AWS
  • Strong collaboration skills, able to manage ambiguity and keep stakeholders aligned
  • Bachelor's degree in Computer Science or a related technical field

Pay

$160,000 – $190,000 annually

Schedule

Remote - US based candidates only, no visa sponsorship available

Benefits

  • Flexible work arrangements with in-office collaboration 1-2 times per quarter
  • Opportunity to work on cutting-edge open-source technologies at a vast scale

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