TL;DR

Dataops Engineer (Advanced Analytics): Design, implement, and operate data and analytics infrastructure and platforms enabling machine learning, generative AI, and advanced analytics with an accent on scalability, reliability, and automation. Focus on building secure, observable, and scalable data pipelines and promoting DataOps and MLOps best practices.

Location: Remote (Colombia), Monterrey, Montevideo

Company

%hirify_global% is an outsourcing company working with global clients, including a leading Latin American airline, delivering software and advanced analytics solutions.

What you will do

Design and maintain infrastructure, tools, and frameworks for data and analytical pipelines.
Ensure scalability, reliability, and observability of data and analytics platforms.
Collaborate with Data Engineering, ML Engineering, and DevOps teams to promote DataOps and MLOps best practices.
Automate data ingestion, orchestration, and monitoring for analytical and ML workflows.
Implement data governance, quality, and versioning practices integrated into operational flows.
Evaluate and deploy new tools and architectures to enhance the data ecosystem.

Requirements

Location: Must be based in Monterrey, Montevideo, or Colombia (remote)
Experience with Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Composer, Vertex AI).
Strong knowledge of Infrastructure as Code (Terraform), containerization (Docker), and CI/CD automation.
Experience with data platforms and tools like Airflow, dbt, MLflow, Great Expectations.
Ability to design secure, observable, and scalable data and analytics solutions.
Experience working in agile and cross-functional teams.

Nice to have

Knowledge of Python and data processing frameworks to support technical teams.

Culture & Benefits

Vacation as per local laws with encouragement to rest properly.
Health insurance support for employees and loved ones.
10 days sick pay without doctor's note, then as per local laws.
Time off for state holidays regardless of client schedule.
Corporate parties and social gatherings.
Technical and everyday problem-solving support at work.