Data Engineer: dbt, Snowflake & AI Analytics

World Business Lenders, Llc; Ciudad de Mendoza; Hybrid; ARS 139,086,000 - 200,903,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

AgileEngine is seeking a Mid-level Data Engineer to design and maintain dbt pipelines and Snowflake data marts behind customer-facing reporting, spend analytics, and AI features. You will work with ingestion/orchestration tools like Airbyte or Prefect, and require 3+ years in data engineering, strong SQL/Python, dimensional modeling, and upper-intermediate English.

You will build production-grade data assets, ensure data quality, and collaborate with cross-functional teams to support analytics,

Qualifications

• 3+ years in analytics engineering, data engineering, or related role with production pipelines.
• Solid dbt experience: modeling, tests, macros, incremental models.
• Strong SQL and Python proficiency; keen on data modeling fundamentals.

Responsibilities

• Build and maintain dbt pipelines, data marts, and warehouse models as production systems.
• Translate procurement business logic into maintainable pipeline code.
• Develop data models within the data mart architecture and suggest improvements.
• Contribute to semantic layer for MCP servers and AI agents to ensure consistent metrics.

Skills

dbt experience

SQL & Python

data modeling

cloud warehouse

ingestion tooling

English proficiency

agentic tooling

programming best practices

Tools

Airbyte

Prefect

Snowflake

FastAPI

S3

Job description

AgileEngine is seeking a Mid-level Data Engineer to design and maintain dbt pipelines and Snowflake data marts behind customer-facing reporting, spend analytics, and AI features. You will work with ingestion/orchestration tools like Airbyte or Prefect, and require 3+ years in data engineering, strong SQL/Python, dimensional modeling, and upper-intermediate English.

You will build production-grade data assets, ensure data quality, and collaborate with cross-functional teams to support analytics,