**Pipeline**: CI/CD (GitLab, GitHub Actions) on merge. Stages: dev (PR/merge), QA (release branch), prod (approval/canary). Build once; promote artifacts (Docker, dbt). Env-specific config (vars, ConfigMaps). Tests per stage; integration in QA. For data: separate DBs; versioned migrations; dbt target....
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 Infosys. The answer also includes follow-up discussion points that interviewers commonly explore.
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