senior-data-engineer

name	senior-data-engineer
description	Data engineering workflows for designing reliable pipelines and datasets: ingestion, transforms, orchestration, schema evolution, data contracts, quality checks, and observability. Use when building ETL/ELT, reviewing pipelines, defining warehouse/lake schemas, or diagnosing data quality incidents.

Senior Data Engineer

Make data pipelines boring: predictable, observable, and recoverable.

Quick Start

1. Define the data contract (schema + semantics + freshness + ownership).
2. Design the pipeline:
   • Inputs, transformations, outputs, backfills, and failure handling
3. Data quality: checks for nulls, ranges, uniqueness, and referential integrity.
4. Operational story: retries, checkpoints, alerting, and lineage.

Optional tool: lightweight profiling for CSV/JSONL

python ~/.codex/skills/senior-data-engineer/scripts/data_quality_scan.py path/to/data.csv --out /tmp/data_profile.json

References

• Data contract template: references/data-contract.md
• Pipeline checklist: references/pipeline-checklist.md