Data Engineer, Platform Engineering
Databricks is seeking a talented Data Engineer to join our core platform team in Amsterdam. This role is central to ensuring the scalability and reliability of our data infrastructure, supporting petabyte-scale operations globally. Key responsibilities include designing, implementing, and optimizing ETL/ELT processes using modern big data tools. You will be responsible for building robust data pipelines, writing high-quality, efficient code primarily in Scala and Python, and managing complex workflows within AWS environments. The ideal candidate has deep expertise in Apache Spark and cloud native architectures (e.g., S3, Glue). This role requires strong analytical skills, meticulous attention to detail, and the ability to collaborate with data scientists and backend engineers to transform raw data into actionable insights for our global client base.
(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)
Preparing
1800
Question set
250
Duration
Permanent
Focus areas
People Also Ask (FAQs)
What is the last date to apply for Data Engineer, Platform Engineering?
The closing date is listed in the official advertisement — apply as early as possible.
How do I apply for Data Engineer, Platform Engineering?
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 Data Engineer, Platform Engineering 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: Spark, Scala, Python, AWS, ETL/ELT, Data Warehousing.
Quick start
Review the job summary, then jump into prep with the same flow used for exam starts.