For junior DA roles and career switchers applying in the next 4–8 weeks

Data Analyst job post checklist (copy/paste)

Turn any JD into must-haves in ~10 minutes — then map each item to evidence.

Generate a roadmap

How to use it (3 steps)

  1. Copy the job post into your notes (e.g. Notion) and mark Required vs Preferred.
  2. Map each required item to evidence: a resume bullet, a dashboard, a notebook, or a slide deck.
  3. Build 2 portfolio projects that cover the most required items (not random projects).
Decision rule: If you're missing several Required items, pause applications and build the 2 projects first.

Checklist template

# Data Analyst job post checklist (copy/paste)

## 1) Required (must-have)
### Skills & tools
- [ ] SQL — evidence: ______________________
- [ ] BI (Tableau/Power BI/Looker) — evidence: ______________________
- [ ] Excel / Sheets — evidence: ______________________
- [ ] Python or R (if mentioned) — evidence: ______________________

### Data stack (if mentioned)
- [ ] Warehouse (BigQuery/Snowflake/Redshift) — evidence: ______________________
- [ ] dbt — evidence: ______________________
- [ ] ETL/ELT (Fivetran/Airflow/etc.) — evidence: ______________________

### Domain / product area
- [ ] Product analytics (funnels/cohorts/retention) — evidence: ______________________
- [ ] Marketing analytics (CAC/LTV/ROAS) — evidence: ______________________
- [ ] E-commerce (Shopify, inventory, merchandising) — evidence: ______________________
- [ ] Finance/ops (revenue, margin, forecasting) — evidence: ______________________

### Deliverables
- [ ] Dashboards (self-serve reporting) — evidence: ______________________
- [ ] KPI definitions + tracking — evidence: ______________________
- [ ] Metric definition (1-page doc) — evidence: ______________________
- [ ] Stakeholder-ready insights (doc or slides) — evidence: ______________________
- [ ] Data cleaning / transformation scripts — evidence: ______________________
- [ ] Experiment analysis (if mentioned) — evidence: ______________________

## 2) Preferred (nice-to-have)
- [ ] Advanced SQL (CTEs/window functions) — evidence: ______________________
- [ ] Experimentation / A/B testing — evidence: ______________________
- [ ] Basic modeling/forecasting — evidence: ______________________
- [ ] Git/version control — evidence: ______________________
- [ ] Cloud (AWS/GCP/Azure) — evidence: ______________________

_Note: Evidence can be a project bullet, screenshot, repo link, or portfolio piece._

## Decision rule
> If you're missing **several Required items**, pause applications and build 2 projects first.

## Portfolio Project 1 (covers most Required)
- Goal: ______________________________________
- Dataset/source: _______________________________
- Deliverables:
  - [ ] SQL queries + clean schema
  - [ ] Dashboard with 5–8 KPIs
  - [ ] Written insights (1–2 pages)

## Portfolio Project 2 (end-to-end narrative)
- Goal: ______________________________________
- Dataset/source: _______________________________
- Deliverables:
  - [ ] Analysis notebook (clean → explore → insight)
  - [ ] Recommendation memo / slides (8–12 slides)
  - [ ] README + assumptions + limitations

Worked examples

Example 1: E-commerce DA (Shopify)
Required: SQL, Shopify, dashboards, KPI tracking, inventory/sales reporting
Preferred: dbt, BigQuery, Fivetran, GA4, Klaviyo
Projects: (1) Shopify Sales & Inventory Dashboard (SQL + BI) (2) Retention Channel ROAS Analysis (GA4/Klaviyo-like dataset + memo)
Evidence mapping: Dashboard link + SQL queries repo + 1-page inventory memo
Example 2: Product Analytics DA
Required: funnels/cohorts, experimentation support, metrics definitions, stakeholder comms
Preferred: Looker, dbt, advanced SQL, Python
Projects: (1) Funnel Drop-off Deep Dive + Dashboard (2) Experiment Readout + recommendation deck
Evidence mapping: Dashboard link + experiment readout deck + metrics doc

Want this auto-filled from your job post?

Must-have breakdown, gap analysis, 2 portfolio projects, and a week-by-week plan.

Generate a roadmap
Free preview • no card • ~2 minutes