Senior Data Engineer — HR Data Warehouse & AI Pipelines

AgileEngine, LLC.; Perímetro Urbano Barranquilla; Híbrido; COP 280.260.000 - 435.961.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive compensation

Exciting projects

Flextime

Descripción de la vacante

AgileEngine, LLC. is seeking a Senior/Lead Data Engineer to build and maintain HR data pipelines in Snowflake, DBT, Python, and Airflow. You will design semantic layers enabling BI tools and AI agents to consume HR data, and explore Cortex-based querying for agentic workflows.

Responsibilities include scalable ETL, data modeling, and implementing data quality tests. Strong SQL, data security, and real-time data processing skills are required; hybrid work options are available.

Formación

• 4+ years of experience in data engineering or related field.
• Strong Snowflake data modeling, datamarts, and warehouse design.
• Proficient DBT data transformations.
• Proficient Python (OO + scripting).
• Airflow for orchestration.
• REST API integration and data ingestion.
• Google BigQuery querying and optimization.
• Secure handling of large-scale sensitive data.

Responsabilidades

• Develop and maintain secure, efficient data pipelines using DBT, PySpark, and Python.
• Build infrastructure for ETL using Python, DBT, Terraform, and AWS (Glue, EMR, S3).
• Monitor pipelines for 99.5% uptime and maintain data models for partners.
• Design semantic views/ontology atop dbt models for BI and AI consumption.
• Develop and deploy AI agents via Snowflake Cortex or related tooling for HR data.

Conocimientos

4+ years exp

Snowflake

DBT

Python

Airflow

REST API

BigQuery

SQL

Herramientas

Terraform

AWS

Descripción del empleo

AgileEngine, LLC. is seeking a Senior/Lead Data Engineer to build and maintain HR data pipelines in Snowflake, DBT, Python, and Airflow. You will design semantic layers enabling BI tools and AI agents to consume HR data, and explore Cortex-based querying for agentic workflows.

Responsibilities include scalable ETL, data modeling, and implementing data quality tests. Strong SQL, data security, and real-time data processing skills are required; hybrid work options are available.