Our dashboards are slow. Pipelines break. Analysts can't trust the data. Data scientists wait days for features. You fix that. As a Senior Data Engineer, you build the pipes, warehouses, and tools that let 2000+ people make data-driven decisions at petabyte scale. If data is late, wrong, or expensive - you feel it. If queries run 10x faster and costs drop 50% - that's also you. What You'll Do
1. Build & Scale Data Pipelines Design, build, and operate batch + real-time pipelines ingesting 1M+ events/sec from app, logs, and 3rd party sources Own data modeling: dimensional, Data Vault, or lakehouse on Iceberg/Hudi/Delta. You decide, you defend Transform messy raw data into clean, tested, documented marts that 1000+ users trust Orchestrate 1000+ DAGs with Airflow: SLAs, retries, backfills, dependency management 2. Platform & Infrastructure Optimize Spark/Flink jobs that process TBs daily. You know when to cache, partition, and when to rewrite in SQL Improve query performance: BigQuery, ...