Real, anonymous reports from people who interviewed for Data Engineer at Fractal, newest first and distilled into what to expect across the loop.
After an online assessment, the timeline got fuzzy. I completed the assessment around mid-February, but there weren’t any official emails afterward with a confirmed interview date. I only saw tentative scheduling details from the company, and even after that step was marked complete, nothing moved forward.
After a recruiter call, my process moved pretty fast into two back-to-back coding interviews. The first coding round focused on DSA in Python/PySpark, and the second one was DSA-style work in SQL. I remember both feeling fairly demanding, but still aligned with core data-engineering fundamentals rather than trick puzzles.
Candidates often begin with an online assessment, but experiences with communication afterward vary significantly, with some reporting delays or lack of clarity on next steps, which can lead to frustration and uncertainty about the process.
The interview process typically includes multiple technical rounds focusing on core data engineering skills, including coding in Python, SQL, and big data technologies like Spark and Azure, with a mix of practical and theoretical questions.
Candidates experience a blend of behavioral and managerial discussions, often aimed at understanding their problem-solving approaches and team dynamics, which follow the technical evaluations to assess fit and collaboration skills.
The overall difficulty of the interviews is generally perceived as intermediate to difficult, with a strong emphasis on practical competency and real-world application of data engineering concepts rather than theoretical knowledge.
While many candidates appreciate the organized structure of the interview process, some report inconsistencies in scheduling and communication, which can impact the overall candidate experience and lead to feelings of disconnection.
Despite many candidates feeling they performed well technically, a significant number did not receive offers, often citing issues related to compensation discussions or lack of timely feedback as contributing factors to their overall experience.