Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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$160к-235к/год
$180к$210кмедиана$230к
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Вакансия дает четкую техническую ответственность за крупную Spark-платформу, но зарплата ниже медианы рынка, а требование работать из одного из указанных офисов ограничивает доступность.
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Ниже рынкаСовременный стекЧеткая зона ответственностиМасштабные задачиПривязка к офису
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Описание вакансии
Текст:
Hirify AI/Оригинал
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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