I use a structured approach: (1) Engineering blogs from companies at scale—Netflix, Uber, Meta, Databricks—for real-world patterns. (2) Conferences—Data+AI Summit, AWS re:Invent—for vendor roadmaps and peer discussions. (3) Communities—Slack (e.g., dbt, Airflow), Reddit—for day-to-day trade-offs. (4) Hands-on—I run POCs or side projects to evaluate tech (e.g., Iceberg, Rust for data). I also share learnings via internal tech talks and design docs....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Presidio. The answer also includes follow-up discussion points that interviewers commonly explore.
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