Pipeline Recipes — HireLens Docs

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# Pipeline Recipes

Ready-to-build pipelines for common hiring intelligence questions.

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## Recipe 1: Top Roles by Demand

**Question:** What are the most in-demand roles right now?

**Pipeline:** Vacancies -> Group By (role) -> Aggregate (COUNT as count) -> Sort (count DESC) -> Limit (10) -> Chart (Bar)

**Steps:**
1. Source: **Vacancies**
2. Group By: `role`
3. Aggregate: COUNT on `id`, alias: `count`
4. Sort: `count` descending
5. Limit: `10`
6. Chart: Bar, label=`role`, value=`count`

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## Recipe 2: Salary by Seniority

**Question:** How does salary scale with experience level?

**Steps:**
1. Source: **Vacancies**
2. Filter: By Salary, min = $1 (excludes zero-salary listings)
3. Group By: `seniority`
4. Aggregate: AVG on `salary_min`, alias: `avg_min`
5. Chart: Bar, label=`seniority`, values=`avg_min`

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## Recipe 3: Remote vs Office Breakdown

**Question:** Is the market shifting towards remote work?

**Steps:**
1. Source: **Vacancies**
2. Group By: `location_type`
3. Aggregate: COUNT on `id`, alias: `total`
4. Chart: Doughnut, label=`location_type`, value=`total`

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## Recipe 4: Hiring Timeline

**Question:** How has vacancy volume changed over time?

**Steps:**
1. Source: **Vacancies**
2. Group By: `created_at` with truncation = `month`
3. Aggregate: COUNT on `id`, alias: `count`
4. Sort: `created_month` ascending
5. Chart: Line, label=`created_month`, value=`count`

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## Recipe 5: Top Hiring Companies

**Question:** Which companies have the most open positions?

**Pipeline:** Vacancies -> Group By (company_name) -> Aggregate (COUNT as openings) -> Sort (openings DESC) -> Limit (15) -> Chart (Bar)

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## Recipe 6: Domain Salary Comparison

**Question:** Which industry domains pay the best?

**Pipeline:** Vacancies -> Filter (salary > 0) -> Group By (domain) -> Aggregate (AVG salary_max as avg_salary) -> Sort (avg_salary DESC) -> Chart (Bar)

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## Recipe 7: Quality Score Distribution

**Question:** What is the overall quality of listings in the market?

**Pipeline:** Vacancies -> Group By (score) -> Aggregate (COUNT as count) -> Sort (score ASC) -> Chart (Bar)

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## Recipe 8: Company Size Breakdown

**Question:** Are startups or enterprises hiring more?

**Pipeline:** Companies -> Group By (company_size) -> Aggregate (COUNT as count) -> Chart (Doughnut)

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## Recipe 9: Seniority by Domain

**Question:** Do DeFi companies hire more seniors than Gaming companies?

**Pipeline:** Vacancies -> Filter (domain = DeFi) -> Group By (seniority) -> Aggregate (COUNT as count) -> Chart (Bar)

Duplicate and modify the filter for other domains to compare side by side.

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## Recipe 10: High-Score Roles

**Question:** Which roles have the highest average quality score?

**Pipeline:** Vacancies -> Group By (role) -> Aggregate (AVG score as avg_score, COUNT as total) -> Sort (avg_score DESC) -> Limit (10) -> Table

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## Tips for Building Recipes

1. **Start simple** — Begin with Source, Group By, Aggregate, Output, then add filters
2. **Check column names** — The Sort dropdown shows exactly what is available from upstream
3. **Use templates** — Load a template, then modify filters and groupings
4. **Chain filters** — Multiple filters narrow progressively
5. **Experiment with chart types** — Same data looks different as bar vs. line vs. doughnut

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