Data / AI Engineer

Nestium; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Nestium is seeking a data engineering professional to build and maintain ingestion pipelines that transform diverse datasets into a consistent, queryable model across Central and Eastern European markets. The role emphasizes validation, freshness checks, and end-to-end provenance in line with GDPR requirements.

The ideal candidate brings hands-on experience with Python and SQL, familiarity with geospatial tools, and a practical, reliability-focused mindset to ensure robust data processing and

Qualifications

• Hands-on experience building production data pipelines in Python and SQL.
• Geospatial tooling experience, especially PostGIS, is a plus.
• Preference for simple, reliable system designs over clever or fragile ones.
• Strong commitment to data provenance, reproducibility, and lawful data handling.

Responsibilities

• Design and run ingestion and structuring pipelines for registries, public statistics, licensed feeds, and signals.
• Add cross-source validation, freshness monitoring, and outlier checks to flag weak or stale inputs.
• Shape the data model to stay comparable and current across markets.
• Maintain provenance and reproducibility from raw input to delivered dataset.

Skills

Python

SQL

Geospatial tooling

Tools

PostGIS

Job description

Role overview

This role builds the data pipelines that transform fragmented public records, licensed feeds, and geospatial inputs into a queryable, comparable data model spanning multiple Central and Eastern European markets. The work emphasizes validation, freshness checks, and end-to-end provenance, with any personal information handled in line with EU GDPR requirements.

Responsibilities

• Design and run ingestion plus structuring pipelines for registries, public statistics, licensed feeds, and assorted signals.
• Layer in cross-source validation, freshness monitoring, and outlier checks so weak or stale inputs are flagged rather than silently propagated.
• Shape the underlying data model so it stays comparable and current across markets.
• Maintain provenance and processing reproducibility from raw input through to delivered dataset.

Requirements

• Hands-on experience building production data pipelines, primarily in Python and SQL.
• Familiarity with geospatial tooling such as PostGIS considered a plus.
• Preference for simple, reliable system designs over clever or fragile ones.
• Strong commitment to data provenance, reproducibility, and lawful data handling.