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10 дней назад

Senior Software Engineer, Spark Platform

159 800 - 235 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Senior Software Engineer, Spark Platform (Apache Spark/Kubernetes): Building and operating an in-house Spark-on-Kubernetes platform for data, analytics, and ML workloads with an accent on distributed systems, runtime optimization, shuffle architecture, and multi-tenant scheduling. Focus on setting multi-year technical direction, solving large-scale reliability and performance problems, and shaping platform architecture across the runtime, scheduler, and observability stack.

Location: Hybrid; must be located in San Francisco, Sunnyvale, Seattle, or New York City, US

Salary: $159,800–$235,000 USD base salary, plus potential equity grants

Company

hirify.global operates a large-scale Apache Spark ecosystem supporting data, analytics, and machine learning workloads.

What you will do

  • Set the multi-year technical direction for the in-house Spark-on-Kubernetes platform, including runtime, shuffle, scheduling, and reliability.
  • Own distributed-systems challenges involving shuffle architecture, multi-tenant scheduling, runtime performance, and large-scale failure modes.
  • Partner with the Engineering Manager on technical roadmaps, hiring, interview design, and team structure.
  • Provide technical leadership through design reviews, mentorship, and engineering quality improvements.
  • Represent Spark Platform in cross-team architecture discussions with Data Engineering, ML Platform, and product engineering.

Requirements

  • Bachelor’s, master’s, or PhD in Computer Science or equivalent experience.
  • 6+ years of industry experience designing and operating distributed systems at scale.
  • Deep hands-on Apache Spark experience, including internals, query execution, shuffle, and the executor/driver model, with platform-scale operations experience.
  • Production experience with Kubernetes, including operator patterns, executor pod lifecycle, network topology, and multi-tenant failure modes.
  • Experience with remote or external shuffle systems, batch or big-data schedulers, or observability and SRE patterns for distributed compute platforms.
  • Professional experience with Scala, Java, Python, or Go, plus strong SQL skills; familiarity with Apache Iceberg, Delta Lake, and query or SQL engines is expected.

Nice to have

  • Experience with Apache Iceberg or Delta Lake and the query engines that read them.
  • Experience operating Spark on Amazon EMR, Databricks, or an in-house deployment.

Culture & Benefits

  • Hybrid work in one of the listed US locations.
  • 401(k) plan with employer matching.
  • Medical, dental, vision, disability, and basic life insurance.
  • Paid parental leave, paid time off, paid sick leave, and 11 paid holidays.
  • Wellness, commuter, family-forming assistance, and mental health benefits.

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