analytics-data-engineer

---
name: analytics-data-engineer
description: |
license: MIT
---

# Analytics Data Engineer

## When to Use

- Structure a **dbt project** (layers, naming, materializations)
- Build **staging → intermediate → mart** pipelines in the warehouse
- Implement **incremental**, snapshot, or CDC-driven models
- Add **tests** (unique, not null, relationships, custom SQL) and freshness checks
- Document models and expose **lineage** for BI and stakeholders
- Define **marts** that map to metrics and dashboards
- Set up **CI** for analytics SQL (compile, test, slim CI)
- Debug **metric mismatches** between mart and dashboard

## When NOT to Use

- Enterprise mesh, governance program, platform selection → `data-architect`
- Partition/cluster tuning without dbt context → `data-warehouse-engineer`
- Chart choice, executive dashboards, stakeholder storytelling → `bi-analyst`
- Feature engineering, training, experiments → `data-scientist`
- Data org roadmap and steward operations → `data-manager`
- Analytics eng hiring, squad roadmap, launch governance → `analytics-data-engineering-manager-product`
- Generic app CI/CD without analytics patterns → `devops`

## Related skills

| Need | Skill |
|---|---|
| Warehouse SQL tuning, star schema theory | `data-warehouse-engineer` |
| KPI definitions and dashboards | `bi-analyst` |
| Platform and domain architecture | `data-architect` |
| Pipeline on-call and platform SLOs | `data-system-ops-lead` |
| ML and advanced stats | `data-scientist` |
| Requirements and metric business rules | `business-analyst` |

## Core Workflows

### 1. Project layout and conventions

Layering, naming (`stg_`, `int_`, `fct_`, `dim_`), materialization defaults, env targets.

**See `references/dbt_project_structure.md`.**

### 2. Modeling for analytics

Facts, dimensions, wide marts, grain, degenerate dimensions, bridge tables.

**See `references/analytics_modeling.md`.**

### 3. Incremental and CDC

Merge strategies, full-refresh exceptions, late-arriving facts.

**See `references/incremental_cdc.md`.**

### 4. Quality and contracts

Tests, severity, source freshness, optional contracts with downstream.

**See `references/testing_quality.md`.**

### 5. Docs, lineage, exposures

Model descriptions, column docs, exposures to BI tools.

**See `references/docs_lineage_exposures.md`.**

### 6. Metrics alignment

Grain, definitions, ownership with `bi-analyst` and `business-analyst`.

**See `references/metrics_alignment.md`.**

## Output standards

- Every mart documents **grain** and **primary key** in YAML
- Tests on keys and critical business rules before merge
- PR includes: models changed, test plan, backfill impact, downstream exposures
- No breaking grain change without migration note to BI

## When to load references

- **dbt layout** → `references/dbt_project_structure.md`
- **Modeling** → `references/analytics_modeling.md`
- **Incremental** → `references/incremental_cdc.md`
- **Tests** → `references/testing_quality.md`
- **Docs/CI** → `references/docs_lineage_exposures.md`
- **Metrics** → `references/metrics_alignment.md`