The process was structured and professional. It started with a recruiter screening where we discussed my experience, especially around data engineering tools like AWS, Python, and Spark. After that, I had a technical phone interview with real-world coding and SQL problems. They focused a lot on data pipeline design, performance tuning, and system design.
Next was the onsite (or virtual onsite) round, which included 4-5 interviews. Each one tested different areas—like cloud data architecture, ETL optimization, and behavioral questions on team leadership and problem-solving. One round was specifically about coding in Python and another was focused on SQL queries and data modeling.
Questions d'entretien [1]
Question 1
They asked me to design a real-time data pipeline that ingests streaming data, processes it, and makes it available for analytics—basically testing my hands-on knowledge with tools like Kafka, Spark Streaming, and AWS services like Kinesis, Glue, and Redshift.
Simple and non technical. No technical questions at all in the initial screening. 3 more interviews after that. Not terrible. All stuff you’ve probably seen before. Some experience and personal questions
J'ai passé un entretien chez Google (Mountain View, CA)
Entretien
recruiter > tech screen on coderpad with advanced sql and some python data manipulation. the onsite was a 5 round loop: data modeling, pipeline design, python coding, advanced sql, and a googleyness/behavioral chat. the pipeline design round is the absolute filter imo - they throw a massive ques at you, like designing a real-time analytics pipeline for ad-click tracking system, and you have to map out the batch vs streaming architecture, idempotency, and how to handle late-arriving data from scratch. the modeling round was all about star schemas, handling slowly changing dimensions (SCDs), and optimizing tables. it felt very practical; it’s more about how you structure data at a massive scale and handle edge cases. for prep, i focused on kimball methodology and practicing streaming architectures. i did a few mocks on Prepfully with google DEs specifically for the pipeline design round and that helped me lot. Skimmed through DataLemur for ques and practice and yeah ofcourse blind/reddit for recent experiences
Questions d'entretien [1]
Question 1
design a data pipeline to process clickstream events from millions of users in real time
J'ai passé un entretien chez Google (Cupertino, CA)
Entretien
Many rounds very The interview process included an initial screening, technical assessment, and behavioral interview focused on communication, problem-solving, teamwork, and adaptability. Final candidates met with leadership to discuss role expectations and organizational fit.
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