Principal Apache Hadoop Engineer

TL;DR

Principal Apache Hadoop Engineer (Backend Dev): Lead design and optimization of large-scale distributed data processing systems using Apache Hadoop and related big data technologies with an accent on HDFS architecture, MapReduce workflows, and YARN resource management. Focus on architecting reliable distributed storage, driving cluster efficiency, contributing to open source, and mentoring engineering teams.

What you will do

• Contribute 20% of time as a core contributor to Apache Hadoop and related open source projects.
• Design and optimize big data ecosystem architectures for large-scale data processing.
• Architect advanced HDFS components for reliable distributed data storage.
• Lead MapReduce paradigm implementation for scalable data workflows.
• Drive YARN resource management optimization for cluster performance.
• Mentor engineering teams and provide technical leadership.

Requirements

• Advanced level of English required.
• 10+ years of software development experience.
• Strong expertise in big data ecosystem and distributed data processing systems.
• Deep understanding of HDFS architecture and distributed file systems.
• Proficiency in MapReduce and parallel processing techniques.
• Proven experience with YARN resource management and cluster orchestration.
• Core contributions to Apache open source projects (Hadoop, HDFS, Spark, or similar).

Culture & Benefits

• Excellent compensation in USD or local currency.
• Paid parental leave, vacation, and national holidays.
• Innovative and multicultural work environment.
• Collaboration with global Top 1% tech talent.
• Supportive environment with mentorship, promotions, and skill development.