Understanding the Company's Infrastructure Context Questions
Research the company's public infrastructure information (engineering blog, tech talks, published case studies, job description). Understand what systems they operate at scale, what problems they likely face, and what your role would contribute to.
MediumTechnical
0 practiced
Technical/SQL task: Given an internal metadata schema in Postgres:datasets(dataset_id INT PRIMARY KEY, name TEXT, size_bytes BIGINT, last_updated TIMESTAMP),jobs(job_id INT, owner TEXT, dataset_id INT, rows_processed BIGINT, run_at TIMESTAMP)Write a SQL query that returns the top 5 datasets by growth rate (delta size over the last 30 days / size 30 days ago) and the distinct list of job owners who wrote to those datasets. Explain briefly how you'd use this output to infer storage hotspots.
EasyBehavioral
0 practiced
Behavioral: Tell me about a time you researched a company's technical stack before an interview or onboarding. Which public sources did you use, what concrete things did you prepare based on that research, and how did it change the outcome of the interview or your first weeks on the job?
HardTechnical
0 practiced
Leadership / roadmap: After reading the company's scaling-focused engineering posts, draft a 6-month roadmap you would present as a Senior/Staff Data Engineer to improve platform reliability and cost efficiency. Include measurable goals (e.g., SLOs, cost reduction %), key initiatives (observability, retention policy, infra automation), resource estimates, and a plan to get cross-functional buy-in.
MediumBehavioral
0 practiced
Behavioral/communication: Give an example of how you would present findings from your public infrastructure research to a hiring manager in an interview to show you understand their stack and can add value. What key points would you emphasize, how would you demonstrate curiosity, and how would you avoid making incorrect assumptions?
MediumSystem Design
0 practiced
An article states the company's largest monthly cost is long-term storage of raw data in object storage. Propose a retention and tiering strategy that balances analyst needs, regulatory retention, and cost: include retention windows, tier mapping (hot/cold/archive), access patterns, lifecycle rules, and how you'd get buy-in from analysts and compliance.
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