Data Engineer

StratifyIQ; Colombia; Presencial; COP 90.000.000 - 130.000.000; Jornada completa

Descripción de la vacante

StratifyIQ is seeking a Data Engineer to join our data team focused on acquiring, normalizing, and standardizing real estate market data. You will help power reporting tools, maps, charts, and widgets embedded on partner sites.

You will own end-to-end data workflows, from ingesting MLS feeds to delivering clean datasets for downstream consumption, while collaborating with product engineering to support data-driven features and visuals.

Formación

• Experience building and maintaining ETL pipelines for real-world, messy datasets.
• Ability to normalize and standardize diverse data sources.
• Comfort owning problems end-to-end, from ambiguity to delivery.

Responsabilidades

• Ingest and normalize real estate market data, including MLS feeds and third-party datasets.
• Build and maintain ETL pipelines feeding reporting, mapping and visualization products.
• Collaborate with product engineering teams to support data-driven features and consumer-facing visuals.

Conocimientos

ETL pipelines

Data modeling

Normalization

Real estate data

End-to-end ownership

Herramientas

Claude Code

Codex

Descripción del empleo

About The Role

We're looking for a data engineer to join a data team responsible for acquiring, normalizing, and standardizing real estate and property market data. That data powers a suite of consumer- and agent-facing products, including reporting tools, maps, charts, and widgets embedded on other websites.

What You'll Work On

• Ingesting and normalizing real estate market data, including MLS feeds (Multiple Listing Service data, the standard source of property listing information used across the real estate industry), along with related third-party data sets.
• Building and maintaining ETL pipelines (Extract, Transform, Load: pulling raw data from its source, cleaning and reshaping it, then loading it into a system others can use) that feed reporting, mapping, and visualization products.
• Partnering with product engineering teams to support data-driven features and consumer-facing visualizations.

What We're Looking For

• A data engineering background, with pipeline and ETL experience, plus normalization and standardization work on real-world, messy data sets.
• Comfortable owning problems end-to-end, even when the specification isn't fully worked out ahead of time.
• An AI-native workflow: comfortable using tools like Claude Code or Codex as part of day-to-day development.