Mid-Level Data Engineer — dbt, Snowflake & AI Pipelines

AgileEngine, LLC.; Metropolitana; Hybrid; COP 90,000,000 - 180,000,000; 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 build dbt pipelines and Snowflake data marts powering reporting, spend analytics, and AI features. 3+ years in data engineering, solid dbt and coding skills, and experience with Airbyte or Prefect are required.

You will own production-grade pipelines, model translation of complex procurement logic, and contribute to semantic layers and AI-backed insights while safeguarding PII and data governance across systems.

Qualifications

• 3+ years in analytics engineering, data engineering, or similar role with production pipelines.
• Solid dbt experience: modeling, tests, macros, and incremental models.
• Strong SQL and working Python; familiarity with data marts and dimensional modeling.
• Experience with a modern cloud warehouse (Snowflake preferred) and data ingestion/orchestration tools.

Responsibilities

• Build and maintain dbt pipelines, data marts, and warehouse models for reporting and analytics.
• Translate business logic into reliable, tested pipeline code; flag questionable results.
• Develop models within data mart architecture and propose improvements.
• Contribute to semantic layer design and ensure consistent metrics across consumers.
• Maintain data boundary for PII and agent/reporting-safe data; build FastAPI services.
• Ingest data (Airbyte, OneSchema, S3) and support Forward Deployed Engineering.
• Implement data quality checks, freshness, schema tests, and alerting.
• Document data lineage and guardrail rationale for future audits.

Skills

dbt experience

SQL

Python

data modeling

Tools

dbt

Airbyte

Prefect

Snowflake

FastAPI

S3

Job description

AgileEngine is seeking a Mid-level Data Engineer to build dbt pipelines and Snowflake data marts powering reporting, spend analytics, and AI features. 3+ years in data engineering, solid dbt and coding skills, and experience with Airbyte or Prefect are required.

You will own production-grade pipelines, model translation of complex procurement logic, and contribute to semantic layers and AI-backed insights while safeguarding PII and data governance across systems.