About the job

We’re working with an early-stage AI company building a next-gen “anti-CRM” for recruitment - and they’re looking for a hands-on Data Migration Engineer to own how customer data flows into the platform.

This isn’t a typical data role.

It’s about taking messy, real-world client data and turning it into something clean, structured, and usable at scale.

What you’ll be doing

• Own end-to-end data migrations (CRMs, ATSs, databases)

• Build ETL / ELT pipelines for ingestion & transformation

• Work with large, messy datasets (cleaning, mapping, structuring)

• Design data models & schemas

• Solve real data quality & integration problems

• Operate in a low-structure, high-ownership environment

What we’re looking for

• ~2–5 years in Data Engineering / ETL / Data Integration

• Strong SQL + Python

• Experience with data pipelines (ETL/ELT)

• Comfortable handling messy, unstructured data

• Exposure to cloud/data stack (AWS, BigQuery, Redshift, etc.)

Bonus

• Data migration experience

• Tools like dbt, Airflow, Fivetran

• CRM / operational data exposure

Why this role

• Early-stage AI product with real traction

• High ownership from day one

• Work directly on the core data layer of the product

• Fast-paced environment where you’ll actually build, not just maintain

If you’re someone who enjoys untangling messy data problems and building clean pipelines from scratch, this is a strong fit.