AI Analytics Engineer — Production AI Pipelines & Equity

Addi; Colombia; Presencial; COP 120.000.000 - 180.000.000; Jornada completa

Descripción de la vacante

Addi is seeking an AI-focused data engineer to own the end-to-end delivery of AI agents within the embedded function, driving measurable business impact from problem identification to production adoption.

You will build self-serve operations, maintain pipelines with dbt and Airflow, design AI-first data models, and collaborate with stakeholders to prioritize opportunities while ensuring reliability and adoption.

Formación

• Proven experience in SQL and data modeling.
• Experience designing data models AI agents can understand and extend.
• Strong SQL skills for large datasets with AI-accelerated validation.
• Experience with AI-assisted testing and data quality validation.
• Experience building Python applications for AI-powered data workflows.
• Track record delivering Python-based pipelines in production.
• Data pipelines spec-first with AI as the execution layer.
• Experience with dbt, Airflow or equivalent orchestration.
• Experience integrating AI into production pipelines with monitoring.
• Proven ability to ship data solutions quickly in ambiguous environments.

Responsabilidades

• Ship AI Agents to Production: identify high-friction workflows and deploy with measurable impact.
• Build a Self-Serve Operations Model: document inputs, outputs, failure modes and resolutions.
• Produce a Prioritized Opportunity Backlog: score problems by friction, feasibility, and impact.
• Continuous Improvement: monitor performance and implement measurable reliability improvements.

Conocimientos

SQL & data modeling

Python for AI

AI-driven data pipelines

Data orchestration

BigQuery / Snowflake / Redshift

Herramientas

dbt

Airflow

Claude Code

LiteLLM

Descripción del empleo

Addi is seeking an AI-focused data engineer to own the end-to-end delivery of AI agents within the embedded function, driving measurable business impact from problem identification to production adoption.

You will build self-serve operations, maintain pipelines with dbt and Airflow, design AI-first data models, and collaborate with stakeholders to prioritize opportunities while ensuring reliability and adoption.