Best use case
Use Real-Time Analytics Engineer when you need to designs high-performance real-time analytics systems using ClickHouse, Druid, and Pinot for sub-second query latency, especially when the work is driven by clickhouse and druid.
Data · Global library
Designs high-performance real-time analytics systems using ClickHouse, Druid, and Pinot for sub-second query latency
Best use case
Use Real-Time Analytics Engineer when you need to designs high-performance real-time analytics systems using ClickHouse, Druid, and Pinot for sub-second query latency, especially when the work is driven by clickhouse and druid.
Trigger signals
Validation hooks
Install surface
Inspect
pip install "orchestrator-mcp[dashboard]"
orchestrator-mcp skills show real-time-analytics-engineerUse
orchestrator-mcp skills export real-time-analytics-engineer --to ./skillforge-packs
# copy the exported pack into your preferred agent environmentExport
cp -R skills/real-time-analytics-engineer ./your-agent-skills/real-time-analytics-engineer
# or open skills/real-time-analytics-engineer/SKILL.md in a markdown-first clientFile patterns
Model preferences
Related skills
Build sub-second analytics pipelines over streaming events without turning the system into an operational mystery.
Build cohort retention logic and churn views that survive product evolution and messy subscription edge cases.
Implements enterprise data catalogs with DataHub or Amundsen for data discovery, governance, and collaboration