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Senior Staff Engineer, Data (Apache Spark)

Формат работы
hybrid
Тип работы
fulltime
Грейд
principal
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 Staff Engineer, Data (Apache Spark): Designing and evolving FloQast's core lakehouse data platform across ingestion, governance, storage, processing, and access with an accent on Apache Spark, Iceberg, Kafka, and cloud-native data systems. Focus on defining distributed compute architecture, scaling reliable batch and streaming pipelines, and establishing platform standards for data quality, security, observability, and cost efficiency.

Location: San Jose, California; hybrid workplace

Company

hirify.global develops a SaaS platform with a core data foundation supporting product, analytics, and business operations.

What you will do

  • Lead the architecture of scalable data pipelines, storage solutions, access layers, and lakehouse systems.
  • Own event streaming, batch and streaming ETL, data cataloging, and foundational data platform components.
  • Define standards for data quality, lineage, privacy, access control, and regulatory compliance.
  • Make compute architecture decisions for a platform supporting more than 30,000 tenants.
  • Collaborate with Product, Analytics, Infrastructure, and Security teams to align platform capabilities with organizational goals.
  • Mentor engineers, establish coding and architecture standards, and evaluate technologies that improve performance, observability, developer experience, and cost efficiency.

Requirements

  • 10+ years of software engineering experience with deep expertise in data infrastructure, distributed systems, or backend platform engineering.
  • Production experience designing data platforms at scale, including hundreds of terabytes of data and thousands of jobs per day.
  • Deep Apache Spark experience, including partitioning, shuffle behavior, memory management, Catalyst optimization, PySpark or Scala Spark, Structured Streaming, and Spark UI debugging.
  • Experience with Apache Iceberg, Kafka, Airflow, Snowflake, dbt, and cloud-native technologies such as AWS, GCP, or Azure.
  • Experience building APIs and services for data access, metadata management, and platform observability.
  • Knowledge of GDPR, SOC2, HIPAA, enterprise security practices, and effective cross-functional communication.

Nice to have

  • Experience in a startup or high-growth SaaS environment.
  • Exposure to AI/ML data pipelines or real-time analytics platforms.

Culture & Benefits

  • Values authenticity, integrity, growth, collaboration, and customer focus.
  • Hybrid engineering environment with opportunities to influence platform strategy and technical standards.
  • Equal-opportunity employment practices and an inclusive professional workplace.

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