Distributed Systems Engineer – Apache Big Data Internals (Remote)

About the role

We are looking for a Distributed Systems Engineer to work on the core internals of Apache big‑data projects. The position is fully remote and focuses on building, debugging, and optimizing the engines themselves rather than end‑user applications.

Key responsibilities

• Write production‑grade code for Apache big‑data projects such as Spark, Flink, Trino, Kafka, Hadoop, and related ecosystems.
• Debug and optimise engine internals—including query planning, distributed execution, scheduling, state management, replication, storage layers, and metadata services—at petabyte scale.
• Shape architectural direction for performance and scalability at the engine layer.
• Profile and tune JVM behaviour (garbage collection, memory layout, concurrency).
• Collaborate with cross‑functional engineering teams and open‑source committers on integrations and ecosystem work.
• Mentor senior engineers and raise the engineering bar through code reviews and design critiques.

Required profile

• 6+ years of professional software development experience.
• Strong Java and/or Scala programming skills.
• Solid experience with distributed systems and concurrent or parallel programming.
• Working knowledge of the internals of at least one Apache big‑data project (e.g., Spark, Flink, Trino, Ozone, Iceberg, Hive, NiFi, Kafka, Hadoop, HBase, Impala, Kudu).
• Familiarity with JVM performance characteristics (GC, memory, threading).
• Advanced proficiency in English.

Required skills

• Java
• Scala
• JVM performance tuning (GC, memory, threading)
• Apache Spark
• Apache Flink
• Apache Trino
• Apache Ozone
• Apache Iceberg
• Apache Hive
• Apache NiFi
• Apache Kafka
• Hadoop
• HBase
• Impala
• Kudu

What we offer

• Fully remote work arrangement.
• Competitive compensation in USD or local currency.
• Hardware and software setup for home office.
• Flexible hours – create your own schedule.
• Paid parental leave, vacation days, and national holidays.