# Example: Build a Sourcing Plan

Fictional company, role and people.

## What the user pasted

> need a sourcing plan asap. Data Engineer @ Larkspur Energy, remote from Spain or Portugal. Must: Python, SQL, building pipelines (Airflow or similar), cloud (AWS pref). Nice: dbt, energy/IoT data. €50–62k. HM is Rui. 1 hire, wants start in ~10 wks. I have maybe 5 hrs/week. We interviewed 2 good people for a similar role in spring, one (C.M.) went elsewhere, other (P.S.) no budget at the time. Don't approach anyone at Voltara (client).

## What the skill produced

# Sourcing plan: Data Engineer, remote from Spain or Portugal

**Hires needed:** 1 · **Target start:** about 10 weeks · **Sourcing time:** 5 hours per week · **Pay:** €50–62k

## Target profiles

| Profile | Titles to search | Skills and tools | Why they fit |
|---|---|---|---|
| A. Data engineer | Data Engineer, Big Data Engineer, ETL Developer | Python, SQL, Airflow, AWS | Direct match on all must-haves |
| B. Analytics engineer moving to engineering | Analytics Engineer, BI Engineer | dbt, SQL, Python | Has the nice-to-have; check pipeline depth |
| C. Backend developer with data work | Backend Engineer, Python Developer | Python, AWS, pipelines, Kafka | Strong Python and cloud; SQL to confirm |

## Adjacent talent pools

- **IoT and telemetry teams (utilities, mobility, manufacturing):** energy-style time-series data · may need Airflow
- **Platform and DevOps engineers who script in Python:** AWS and automation · may need SQL modelling and Airflow
- **Returners with past data engineering work:** Python, SQL and pipelines · may need a refresher on current tools

## Warm sources first

- **Silver medallists:** P.S. (no budget last time). Contact first. C.M. took another job in spring; a short "how is it going" note, no pressure.
- **Past applicants:** search your applicant tracking system for "data engineer" applicants from the last 12 months.
- **Referrals:** ask the data team: "Who is the best pipeline engineer you have worked with in Spain or Portugal?"

## Search strings

**Profile A, LinkedIn Boolean**
```
("data engineer" OR "big data engineer" OR "ETL developer") AND python AND SQL AND (airflow OR dagster OR prefect) AND (AWS OR "amazon web services")
```

**Google X-ray**
```
site:linkedin.com/in ("data engineer") (airflow OR dagster) (AWS) (Portugal OR Spain OR Lisboa OR Porto OR Madrid OR Barcelona) -Voltara
```

**Adjacent pool (IoT)**
```
("backend engineer" OR "data engineer" OR "software engineer") AND (IoT OR telemetry OR "time series" OR "smart meter") AND python
```

Set location filters to Spain and Portugal. Exclude current Voltara employees in the company filter.

## Outreach drafts (recruiter to review and send)

**Message 1: The work**
Hi [name], I saw your [pipeline / Airflow project]. At Larkspur Energy we are building data pipelines for [TBC: short product detail]. We are hiring a Data Engineer, remote from Spain or Portugal, €50–62k, travel [TBC]. Open to a 15-minute call to hear more? How we use your data: [Link: privacy notice]

**Message 2: Growth**
Hi [name], your move from [analytics] into [engineering] caught my eye. Our Data Engineer role builds data pipelines with Python and SQL, on AWS [TBC: confirm stack]. Remote from Spain or Portugal, €50–62k, travel [TBC]. Worth a short chat? How we use your data: [Link: privacy notice]

**Follow-up (after 5 working days)**
Hi [name], a quick follow-up in case my note got buried: Data Engineer at Larkspur Energy, remote from Spain or Portugal, €50–62k, travel [TBC]. Happy to send the job description first if that is easier.

## Weekly activity plan

| Activity | Week 1 | Week 2 | Week 3 | Week 4 |
|---|---|---|---|---|
| Contact silver medallists and send referral ask | Done | — | — | — |
| Profiles reviewed | 60 | 50 | 50 | 40 |
| Messages sent | 25 | 25 | 25 | 25 |
| Follow-ups | — | Week 1 non-replies | Week 2 non-replies | Week 3 non-replies |
| Check-in with Rui | First 10 profiles | — | Pipeline review | — |

## Funnel targets (assumptions to adjust)

| Step | Assumed rate | Number needed |
|---|---|---|
| Messages sent | — | 100 |
| Replies | 20% | 20 |
| Recruiter screens | 50% of replies | 10 |
| Shortlist to Rui | 40% of screens | 4 |
| Hire | 1 in 4 | 1 |

About 4 weeks of outreach at 25 messages a week. Replace these rates with your own numbers after week 2.

## Risks and what to try next

- Reply rate under 10% after 50 messages → switch the lead message angle, or ask Rui to share a post.
- Few profiles with Airflow and AWS → accept similar tools (Dagster, GCP) and check with Rui.
- 5 hours a week is tight for a 10-week start → start with warm sources and referrals.

## Open questions

- What product detail can the messages share, and which tools are in the stack? [TBC]
- Is any travel needed? [TBC]
- Is right to work in Spain or Portugal required, or is sponsorship possible? [TBC]
- Which privacy notice link should the messages use for sourced candidates? [TBC]