Staff Software Engineer - Distributed Data Systems
We are hiring an experienced Staff Software Engineer to join our rapidly growing team in Belgrade. This role focuses on enhancing the backbone of our data platform, demanding mastery of large-scale distributed systems principles and fault tolerance design. You will be responsible for owning major components that handle massive data throughput from various sources globally. Core responsibilities include system design reviews, performance tuning, optimizing resource utilization (compute and memory), and developing robust APIs for internal consumption. Expertise in languages like Scala or Java, coupled with practical experience using tools like Kafka, Spark, and Kubernetes, is highly valued. This role offers a direct path to impact the global standard of data processing.
(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)
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2560
Fragensatz
300
Dauer
Permanent
Schwerpunkte
People Also Ask (FAQs)
What is the last date to apply for Staff Software Engineer - Distributed Data Systems?
The closing date is listed in the official advertisement — apply as early as possible.
How do I apply for Staff Software Engineer - Distributed Data Systems?
Use the official apply link on this page to submit your application. A step-by-step how-to-apply guide for this job is also linked below.
Is there negative marking in the Databricks test?
The marking rule is announced per test in the advertisement and roll-number-slip instructions. Many MCQ screening tests have no negative marking, but always verify it for your specific test.
What is the passing marks for this test?
The official passing marks are generally 50%, but merit is competitive — scoring above 75% is a safer target to secure an interview call.
How can I prepare for the Staff Software Engineer - Distributed Data Systems test?
Prepare with the free subject-wise MCQs, past papers and timed mock tests on PrepPro Academy — every question includes the answer with an explanation. Focus areas: Distributed Computing, Scala/Java, Networking Protocols, Apache Spark.
Schnellstart
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